30
7/25/2019 PIJPSM-05-2015-0064 http://slidepdf.com/reader/full/pijpsm-05-2015-0064 1/30  Policing: An International Journal of Police Strategies & Management Exploring how an area's crime-to-cop ratios impact patrol officer productivity Luke Bonkiewicz  Article information: To cite this document: Luke Bonkiewicz , (2016),"Exploring how an area's crime-to-cop ratios impact patrol officer productivity", Policing: An International Journal of Police Strategies & Management, Vol. 39 Iss 1 pp. - Permanent link to this document: http://dx.doi.org/10.1108/PIJPSM-05-2015-0064 Downloaded on: 31 January 2016, At: 09:21 (PT) References: this document contains references to 0 other documents. To copy this document: [email protected] Access to this document was granted through an Emerald subscription provided by emerald-srm:198375 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information.  About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. *Related content and download information correct at time of download.

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Policing An International Journal of Police Strategies amp ManagementExploring how an areas crime-to-cop ratios impact patrol officer productivity

Luke Bonkiewicz

Ar tic le informationTo cite this documentLuke Bonkiewicz (2016)Exploring how an areas crime-to-cop ratios impact patrol officer productivity Policing AnInternational Journal of Police Strategies amp Management Vol 39 Iss 1 pp -Permanent link to this documenthttpdxdoiorg101108PIJPSM-05-2015-0064

Downloaded on 31 January 2016 At 0921 (PT)

References this document contains references to 0 other documents

To copy this document permissionsemeraldinsightcom

Access to this document was granted through an Emerald subscription provided by emerald-srm198375 []

For AuthorsIf you would like to write for this or any other Emerald publication then please use our Emerald for Authors serviceinformation about how to choose which publication to write for and submission guidelines are available for all Pleasevisit wwwemeraldinsightcomauthors for more information

About Emerald wwwemeraldinsightcom

Emerald is a global publisher linking research and practice to the benefit of society The company manages a portfolio of more than 290 journals and over 2350 books and book series volumes as well as providing an extensive range of onlineproducts and additional customer resources and services

Emerald is both COUNTER 4 and TRANSFER compliant The organization is a partner of the Committee on PublicationEthics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation

Related content and download information correct at time of download

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 230

Introduction

Perhaps no civil servant undertakes the variety of tasks as a municipal police officer As

not only law enforcement agents but also community caretakers and first-responders to every

calamity great and small patrol officers handle a broad array of calls for service during their

daily tour of duty The regular duties of a patrol officer include reactive tasks such as handling

calls for service as well as proactive tasks such as conducting traffic and scofflaw enforcement

searching for suspected perpetrators and patrolling for suspicious individuals or situations (eg

drug deals graffiti vandalisms or individuals lsquocasingrsquo a potential target)

Historically both police researchers and practitioners have grappled with the lack of a

valid and reliable method for evaluating patrol officer activity as well as limited knowledge

about how external factors affect officersrsquo productivity (Crank 1990 Johnson 2011 Shane

2010) Although studies have demonstrated that differences in productivity between patrol

officers may result from biographical factors and daily work experiences (Shane 2011)

operational variables (Amaranto et al 2003) and organizational stressors (Brown amp Campbell

1990) scholars have devoted considerably less attention to how the characteristics of an area

might impact police productivity In other words although individual-level variables impact a

patrol officerrsquos productivity how might the characteristics of a patrol area affect a police

officerrsquos productivity

This paper identifies and analyzes two macro-level correlates of patrol officer

productivity violent crimes per officer and property crimes per officer We first review the

extant literature on patrol officer productivity discussing how an arearsquos violent and property

crime per cop ratios might affect a patrol officerrsquos productivity Next we analyze productivity

data from a mid-sized US police department to examine how these two variables impact the

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number of traffic citations warrants and misdemeanor and felony arrests generated by officers

annually We also examine the relationship between these two variables and a more

sophisticated productivity metric Value Over Replacement Cop (VORC) Finally we discuss

why police scholars and practitioners should pay closer attention to the practical macro-level

correlates of productivity as well as incorporate more advanced patrol productivity metrics

Literature Review

Productivity scholars have generally divided the concept of worker productivity into two

spheres (Hatry 1976) Effectiveness measures a worker or organizationrsquos quality of service

while efficiency gauges how well a worker or organization produces a particular output using the

least amount of resources such as manpower time and money Most police research has

examined productivity in terms of efficiency due mainly to the data available for analysis such

as calls for service and arrests

Police scholars have struggled with how to properly measure patrol officer productivity

There appear to be two main approaches The first approach attempts to identify and quantify

specific types of patrol productivity outputs Some examples include evaluating productivity

using an officerrsquos total arrests (Crank 1990) clearance rates (Marciano amp Heaton 2010)

number of traffic citations (Johnson 2011) and citizen complaints (Lersch 2002) However

researchers have noted that evaluating productivity using these kinds of raw outputs is

ldquoconceptually-simplerdquo shaped primarily by data availability (Chappell MacDonald amp Manz

2006)

The second approach to analyzing patrol officer productivity has incorporated multi-

dimensional indicators of police performance For example Shane (2011) conceptualized

productivity using a z-score summary of multiple outputs including arrests traffic citations

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field contacts official reports sick hours and administrative complaints Similarly Van Meterrsquos

Performance-Based Management or ldquozero-based approachrdquo (Van Meter 2001) uses three planks

(non-scheduled absenteeism cost of preventable error and productive use of time) to evaluate

patrol officers

Notably most existing police productivity research has ignored the concept of productive

time or the amount of time officers have for self-initiated activities after handling calls for

service investigating crimes completing reports and follow-ups and assisting other officers

Using productive time to evaluate officers is critical because two officers could achieve the same

output (in terms of raw arrests or reports) but have done so with considerably different amounts

of productive time due to calls for service follow-ups etc Recent research has proposed the use

of Value Over Replacement Cop or VORC (Bonkiewicz 2015) a metric that incorporates more

than a dozen patrol activities weights those activities evaluates performance in terms of

productive time and compares an officerrsquos performance against a fixed hypothetical estimate

(ie a replacement officer)

In addition to conceptualizing patrol officer productivity researchers have also studied

potential antecedents of productivity including not only biographical variables but also factors

involving workplace environment First certain biographical characteristics might impact

productivity (Hawkins 2001) For instance officers who have children might experience sleep

deprivation and greater fatigue as a result of parenting responsibilities thereby reducing their

workplace energy and motivation and in turn their productivity (Shane 2010) Marital status

may also impact productivity Although the relationship between marriage and worker

productivity is well debated in the literature (Nakosteen amp Zimmer 2001 Becker 1985) it

seems reasonable to believe that married officers might be more productive than unmarried

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officers Married officers have someone in whom to confide a partner who hears about the

challenges and rigors of the job which may lead to stress reduction and improve workplace

motivation An officerrsquos age is another consideration Older officers might be less productive

than younger officers perhaps due to burnout as well as the physical demands of law

enforcement (Goodman 1990) Officersrsquo perceptions of their job may also affect their

proactivity and in turn productivity Brehm and Gates (1993) found that officers who disliked

certain aspects of law enforcement (eg taking people to jail) impacted whether officers engaged

in proactive activities or shirked their duties

Additionally there are also operational features (the ldquoday to dayrdquo rigors) of law

enforcement which can decrease productivity and increase misconduct such as the perceived

danger of the job (Amaranto et al 2003) work schedules and shift work (Vila Morrison amp

Kenney 2002) and fatigue (Vila amp Kenney 2002) Notably in studying the relationship

between daily work experience and performance Shane (2011) found that workload was the

ldquomost important predictor of performancerdquo (p 13)

We believe this last finding merits further study First supervisors evaluate patrol

officers at least in part using productivity outputs If there are factors (ie heavy workload)

beyond an officerrsquos control that are affecting his or her productivity both line-level supervisors

and command staff members should acknowledge and account for these variables during

performance reviews Second if macro-level variables create different workloads thereby

affecting productivity outputs then police researchers should include these measures in future

studies on police activity We suggest that there are at least two macro-level variables important

to future police productivity research

Crime-to-Cop Ratios and Patrol Officer Productivity

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Criminological research has long recognized that crime rates are not uniform across

neighborhoods and cities (Sherman et al 1989 Weisburd et al 1993) Instead of ldquopolicing

peoplerdquo law enforcement agencies frequently identify ldquohot spotsrdquo and devote additional

resources to reducing crime and disorder in specific problem areas With this perspective in

mind it might seem natural to examine the relationship between the crime rate of a patrol area

and an officerrsquos productivity outputs (or vice-versa) For example a high crime area might net

an officer more arrests (and therefore more productivity outputs) than a low crime area On the

other hand a high crime area might also occupy a great deal of an officerrsquos productive time

prohibiting the officer from engaging in proactive activities However crime rate does not fully

capture how a particular area might affect an officerrsquos productivity

Instead we believe macro-level variables related to crime should be estimated in terms of

the number of patrol officers in a patrol area specifically violent crimes per officer and property

crimes per officer For instance some officers may patrol a lower crime area but end up

responding to a greater number of violent crimes than officers in a high crime area simply

because they have fewer officers working the street This ldquocrime per coprdquo ratio can dramatically

affect officersrsquo productivity

For example when an officer investigates a crime he or she might interview the victim

suspect and witnesses as well as take photographs collect evidence and make an arrest There

may be additional follow-up the next day or week such as checking pawnshops for stolen

property or tracking down and interviewing additional witnesses All these activities could

decrease an officerrsquos time for self-initiated activities and in turn an officerrsquos overall

productivity A high crime per cop ratio therefore could decrease productivity for officers even

if these officers work in an area with a low crime rate Furthermore an arearsquos crime per cop

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

7252019 PIJPSM-05-2015-0064

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

7252019 PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

7252019 PIJPSM-05-2015-0064

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

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6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

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10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

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983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 2: PIJPSM-05-2015-0064

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Introduction

Perhaps no civil servant undertakes the variety of tasks as a municipal police officer As

not only law enforcement agents but also community caretakers and first-responders to every

calamity great and small patrol officers handle a broad array of calls for service during their

daily tour of duty The regular duties of a patrol officer include reactive tasks such as handling

calls for service as well as proactive tasks such as conducting traffic and scofflaw enforcement

searching for suspected perpetrators and patrolling for suspicious individuals or situations (eg

drug deals graffiti vandalisms or individuals lsquocasingrsquo a potential target)

Historically both police researchers and practitioners have grappled with the lack of a

valid and reliable method for evaluating patrol officer activity as well as limited knowledge

about how external factors affect officersrsquo productivity (Crank 1990 Johnson 2011 Shane

2010) Although studies have demonstrated that differences in productivity between patrol

officers may result from biographical factors and daily work experiences (Shane 2011)

operational variables (Amaranto et al 2003) and organizational stressors (Brown amp Campbell

1990) scholars have devoted considerably less attention to how the characteristics of an area

might impact police productivity In other words although individual-level variables impact a

patrol officerrsquos productivity how might the characteristics of a patrol area affect a police

officerrsquos productivity

This paper identifies and analyzes two macro-level correlates of patrol officer

productivity violent crimes per officer and property crimes per officer We first review the

extant literature on patrol officer productivity discussing how an arearsquos violent and property

crime per cop ratios might affect a patrol officerrsquos productivity Next we analyze productivity

data from a mid-sized US police department to examine how these two variables impact the

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number of traffic citations warrants and misdemeanor and felony arrests generated by officers

annually We also examine the relationship between these two variables and a more

sophisticated productivity metric Value Over Replacement Cop (VORC) Finally we discuss

why police scholars and practitioners should pay closer attention to the practical macro-level

correlates of productivity as well as incorporate more advanced patrol productivity metrics

Literature Review

Productivity scholars have generally divided the concept of worker productivity into two

spheres (Hatry 1976) Effectiveness measures a worker or organizationrsquos quality of service

while efficiency gauges how well a worker or organization produces a particular output using the

least amount of resources such as manpower time and money Most police research has

examined productivity in terms of efficiency due mainly to the data available for analysis such

as calls for service and arrests

Police scholars have struggled with how to properly measure patrol officer productivity

There appear to be two main approaches The first approach attempts to identify and quantify

specific types of patrol productivity outputs Some examples include evaluating productivity

using an officerrsquos total arrests (Crank 1990) clearance rates (Marciano amp Heaton 2010)

number of traffic citations (Johnson 2011) and citizen complaints (Lersch 2002) However

researchers have noted that evaluating productivity using these kinds of raw outputs is

ldquoconceptually-simplerdquo shaped primarily by data availability (Chappell MacDonald amp Manz

2006)

The second approach to analyzing patrol officer productivity has incorporated multi-

dimensional indicators of police performance For example Shane (2011) conceptualized

productivity using a z-score summary of multiple outputs including arrests traffic citations

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field contacts official reports sick hours and administrative complaints Similarly Van Meterrsquos

Performance-Based Management or ldquozero-based approachrdquo (Van Meter 2001) uses three planks

(non-scheduled absenteeism cost of preventable error and productive use of time) to evaluate

patrol officers

Notably most existing police productivity research has ignored the concept of productive

time or the amount of time officers have for self-initiated activities after handling calls for

service investigating crimes completing reports and follow-ups and assisting other officers

Using productive time to evaluate officers is critical because two officers could achieve the same

output (in terms of raw arrests or reports) but have done so with considerably different amounts

of productive time due to calls for service follow-ups etc Recent research has proposed the use

of Value Over Replacement Cop or VORC (Bonkiewicz 2015) a metric that incorporates more

than a dozen patrol activities weights those activities evaluates performance in terms of

productive time and compares an officerrsquos performance against a fixed hypothetical estimate

(ie a replacement officer)

In addition to conceptualizing patrol officer productivity researchers have also studied

potential antecedents of productivity including not only biographical variables but also factors

involving workplace environment First certain biographical characteristics might impact

productivity (Hawkins 2001) For instance officers who have children might experience sleep

deprivation and greater fatigue as a result of parenting responsibilities thereby reducing their

workplace energy and motivation and in turn their productivity (Shane 2010) Marital status

may also impact productivity Although the relationship between marriage and worker

productivity is well debated in the literature (Nakosteen amp Zimmer 2001 Becker 1985) it

seems reasonable to believe that married officers might be more productive than unmarried

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officers Married officers have someone in whom to confide a partner who hears about the

challenges and rigors of the job which may lead to stress reduction and improve workplace

motivation An officerrsquos age is another consideration Older officers might be less productive

than younger officers perhaps due to burnout as well as the physical demands of law

enforcement (Goodman 1990) Officersrsquo perceptions of their job may also affect their

proactivity and in turn productivity Brehm and Gates (1993) found that officers who disliked

certain aspects of law enforcement (eg taking people to jail) impacted whether officers engaged

in proactive activities or shirked their duties

Additionally there are also operational features (the ldquoday to dayrdquo rigors) of law

enforcement which can decrease productivity and increase misconduct such as the perceived

danger of the job (Amaranto et al 2003) work schedules and shift work (Vila Morrison amp

Kenney 2002) and fatigue (Vila amp Kenney 2002) Notably in studying the relationship

between daily work experience and performance Shane (2011) found that workload was the

ldquomost important predictor of performancerdquo (p 13)

We believe this last finding merits further study First supervisors evaluate patrol

officers at least in part using productivity outputs If there are factors (ie heavy workload)

beyond an officerrsquos control that are affecting his or her productivity both line-level supervisors

and command staff members should acknowledge and account for these variables during

performance reviews Second if macro-level variables create different workloads thereby

affecting productivity outputs then police researchers should include these measures in future

studies on police activity We suggest that there are at least two macro-level variables important

to future police productivity research

Crime-to-Cop Ratios and Patrol Officer Productivity

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Criminological research has long recognized that crime rates are not uniform across

neighborhoods and cities (Sherman et al 1989 Weisburd et al 1993) Instead of ldquopolicing

peoplerdquo law enforcement agencies frequently identify ldquohot spotsrdquo and devote additional

resources to reducing crime and disorder in specific problem areas With this perspective in

mind it might seem natural to examine the relationship between the crime rate of a patrol area

and an officerrsquos productivity outputs (or vice-versa) For example a high crime area might net

an officer more arrests (and therefore more productivity outputs) than a low crime area On the

other hand a high crime area might also occupy a great deal of an officerrsquos productive time

prohibiting the officer from engaging in proactive activities However crime rate does not fully

capture how a particular area might affect an officerrsquos productivity

Instead we believe macro-level variables related to crime should be estimated in terms of

the number of patrol officers in a patrol area specifically violent crimes per officer and property

crimes per officer For instance some officers may patrol a lower crime area but end up

responding to a greater number of violent crimes than officers in a high crime area simply

because they have fewer officers working the street This ldquocrime per coprdquo ratio can dramatically

affect officersrsquo productivity

For example when an officer investigates a crime he or she might interview the victim

suspect and witnesses as well as take photographs collect evidence and make an arrest There

may be additional follow-up the next day or week such as checking pawnshops for stolen

property or tracking down and interviewing additional witnesses All these activities could

decrease an officerrsquos time for self-initiated activities and in turn an officerrsquos overall

productivity A high crime per cop ratio therefore could decrease productivity for officers even

if these officers work in an area with a low crime rate Furthermore an arearsquos crime per cop

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

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10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 3: PIJPSM-05-2015-0064

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number of traffic citations warrants and misdemeanor and felony arrests generated by officers

annually We also examine the relationship between these two variables and a more

sophisticated productivity metric Value Over Replacement Cop (VORC) Finally we discuss

why police scholars and practitioners should pay closer attention to the practical macro-level

correlates of productivity as well as incorporate more advanced patrol productivity metrics

Literature Review

Productivity scholars have generally divided the concept of worker productivity into two

spheres (Hatry 1976) Effectiveness measures a worker or organizationrsquos quality of service

while efficiency gauges how well a worker or organization produces a particular output using the

least amount of resources such as manpower time and money Most police research has

examined productivity in terms of efficiency due mainly to the data available for analysis such

as calls for service and arrests

Police scholars have struggled with how to properly measure patrol officer productivity

There appear to be two main approaches The first approach attempts to identify and quantify

specific types of patrol productivity outputs Some examples include evaluating productivity

using an officerrsquos total arrests (Crank 1990) clearance rates (Marciano amp Heaton 2010)

number of traffic citations (Johnson 2011) and citizen complaints (Lersch 2002) However

researchers have noted that evaluating productivity using these kinds of raw outputs is

ldquoconceptually-simplerdquo shaped primarily by data availability (Chappell MacDonald amp Manz

2006)

The second approach to analyzing patrol officer productivity has incorporated multi-

dimensional indicators of police performance For example Shane (2011) conceptualized

productivity using a z-score summary of multiple outputs including arrests traffic citations

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field contacts official reports sick hours and administrative complaints Similarly Van Meterrsquos

Performance-Based Management or ldquozero-based approachrdquo (Van Meter 2001) uses three planks

(non-scheduled absenteeism cost of preventable error and productive use of time) to evaluate

patrol officers

Notably most existing police productivity research has ignored the concept of productive

time or the amount of time officers have for self-initiated activities after handling calls for

service investigating crimes completing reports and follow-ups and assisting other officers

Using productive time to evaluate officers is critical because two officers could achieve the same

output (in terms of raw arrests or reports) but have done so with considerably different amounts

of productive time due to calls for service follow-ups etc Recent research has proposed the use

of Value Over Replacement Cop or VORC (Bonkiewicz 2015) a metric that incorporates more

than a dozen patrol activities weights those activities evaluates performance in terms of

productive time and compares an officerrsquos performance against a fixed hypothetical estimate

(ie a replacement officer)

In addition to conceptualizing patrol officer productivity researchers have also studied

potential antecedents of productivity including not only biographical variables but also factors

involving workplace environment First certain biographical characteristics might impact

productivity (Hawkins 2001) For instance officers who have children might experience sleep

deprivation and greater fatigue as a result of parenting responsibilities thereby reducing their

workplace energy and motivation and in turn their productivity (Shane 2010) Marital status

may also impact productivity Although the relationship between marriage and worker

productivity is well debated in the literature (Nakosteen amp Zimmer 2001 Becker 1985) it

seems reasonable to believe that married officers might be more productive than unmarried

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officers Married officers have someone in whom to confide a partner who hears about the

challenges and rigors of the job which may lead to stress reduction and improve workplace

motivation An officerrsquos age is another consideration Older officers might be less productive

than younger officers perhaps due to burnout as well as the physical demands of law

enforcement (Goodman 1990) Officersrsquo perceptions of their job may also affect their

proactivity and in turn productivity Brehm and Gates (1993) found that officers who disliked

certain aspects of law enforcement (eg taking people to jail) impacted whether officers engaged

in proactive activities or shirked their duties

Additionally there are also operational features (the ldquoday to dayrdquo rigors) of law

enforcement which can decrease productivity and increase misconduct such as the perceived

danger of the job (Amaranto et al 2003) work schedules and shift work (Vila Morrison amp

Kenney 2002) and fatigue (Vila amp Kenney 2002) Notably in studying the relationship

between daily work experience and performance Shane (2011) found that workload was the

ldquomost important predictor of performancerdquo (p 13)

We believe this last finding merits further study First supervisors evaluate patrol

officers at least in part using productivity outputs If there are factors (ie heavy workload)

beyond an officerrsquos control that are affecting his or her productivity both line-level supervisors

and command staff members should acknowledge and account for these variables during

performance reviews Second if macro-level variables create different workloads thereby

affecting productivity outputs then police researchers should include these measures in future

studies on police activity We suggest that there are at least two macro-level variables important

to future police productivity research

Crime-to-Cop Ratios and Patrol Officer Productivity

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Criminological research has long recognized that crime rates are not uniform across

neighborhoods and cities (Sherman et al 1989 Weisburd et al 1993) Instead of ldquopolicing

peoplerdquo law enforcement agencies frequently identify ldquohot spotsrdquo and devote additional

resources to reducing crime and disorder in specific problem areas With this perspective in

mind it might seem natural to examine the relationship between the crime rate of a patrol area

and an officerrsquos productivity outputs (or vice-versa) For example a high crime area might net

an officer more arrests (and therefore more productivity outputs) than a low crime area On the

other hand a high crime area might also occupy a great deal of an officerrsquos productive time

prohibiting the officer from engaging in proactive activities However crime rate does not fully

capture how a particular area might affect an officerrsquos productivity

Instead we believe macro-level variables related to crime should be estimated in terms of

the number of patrol officers in a patrol area specifically violent crimes per officer and property

crimes per officer For instance some officers may patrol a lower crime area but end up

responding to a greater number of violent crimes than officers in a high crime area simply

because they have fewer officers working the street This ldquocrime per coprdquo ratio can dramatically

affect officersrsquo productivity

For example when an officer investigates a crime he or she might interview the victim

suspect and witnesses as well as take photographs collect evidence and make an arrest There

may be additional follow-up the next day or week such as checking pawnshops for stolen

property or tracking down and interviewing additional witnesses All these activities could

decrease an officerrsquos time for self-initiated activities and in turn an officerrsquos overall

productivity A high crime per cop ratio therefore could decrease productivity for officers even

if these officers work in an area with a low crime rate Furthermore an arearsquos crime per cop

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

7252019 PIJPSM-05-2015-0064

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2430

References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

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983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

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C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 4: PIJPSM-05-2015-0064

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field contacts official reports sick hours and administrative complaints Similarly Van Meterrsquos

Performance-Based Management or ldquozero-based approachrdquo (Van Meter 2001) uses three planks

(non-scheduled absenteeism cost of preventable error and productive use of time) to evaluate

patrol officers

Notably most existing police productivity research has ignored the concept of productive

time or the amount of time officers have for self-initiated activities after handling calls for

service investigating crimes completing reports and follow-ups and assisting other officers

Using productive time to evaluate officers is critical because two officers could achieve the same

output (in terms of raw arrests or reports) but have done so with considerably different amounts

of productive time due to calls for service follow-ups etc Recent research has proposed the use

of Value Over Replacement Cop or VORC (Bonkiewicz 2015) a metric that incorporates more

than a dozen patrol activities weights those activities evaluates performance in terms of

productive time and compares an officerrsquos performance against a fixed hypothetical estimate

(ie a replacement officer)

In addition to conceptualizing patrol officer productivity researchers have also studied

potential antecedents of productivity including not only biographical variables but also factors

involving workplace environment First certain biographical characteristics might impact

productivity (Hawkins 2001) For instance officers who have children might experience sleep

deprivation and greater fatigue as a result of parenting responsibilities thereby reducing their

workplace energy and motivation and in turn their productivity (Shane 2010) Marital status

may also impact productivity Although the relationship between marriage and worker

productivity is well debated in the literature (Nakosteen amp Zimmer 2001 Becker 1985) it

seems reasonable to believe that married officers might be more productive than unmarried

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officers Married officers have someone in whom to confide a partner who hears about the

challenges and rigors of the job which may lead to stress reduction and improve workplace

motivation An officerrsquos age is another consideration Older officers might be less productive

than younger officers perhaps due to burnout as well as the physical demands of law

enforcement (Goodman 1990) Officersrsquo perceptions of their job may also affect their

proactivity and in turn productivity Brehm and Gates (1993) found that officers who disliked

certain aspects of law enforcement (eg taking people to jail) impacted whether officers engaged

in proactive activities or shirked their duties

Additionally there are also operational features (the ldquoday to dayrdquo rigors) of law

enforcement which can decrease productivity and increase misconduct such as the perceived

danger of the job (Amaranto et al 2003) work schedules and shift work (Vila Morrison amp

Kenney 2002) and fatigue (Vila amp Kenney 2002) Notably in studying the relationship

between daily work experience and performance Shane (2011) found that workload was the

ldquomost important predictor of performancerdquo (p 13)

We believe this last finding merits further study First supervisors evaluate patrol

officers at least in part using productivity outputs If there are factors (ie heavy workload)

beyond an officerrsquos control that are affecting his or her productivity both line-level supervisors

and command staff members should acknowledge and account for these variables during

performance reviews Second if macro-level variables create different workloads thereby

affecting productivity outputs then police researchers should include these measures in future

studies on police activity We suggest that there are at least two macro-level variables important

to future police productivity research

Crime-to-Cop Ratios and Patrol Officer Productivity

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Criminological research has long recognized that crime rates are not uniform across

neighborhoods and cities (Sherman et al 1989 Weisburd et al 1993) Instead of ldquopolicing

peoplerdquo law enforcement agencies frequently identify ldquohot spotsrdquo and devote additional

resources to reducing crime and disorder in specific problem areas With this perspective in

mind it might seem natural to examine the relationship between the crime rate of a patrol area

and an officerrsquos productivity outputs (or vice-versa) For example a high crime area might net

an officer more arrests (and therefore more productivity outputs) than a low crime area On the

other hand a high crime area might also occupy a great deal of an officerrsquos productive time

prohibiting the officer from engaging in proactive activities However crime rate does not fully

capture how a particular area might affect an officerrsquos productivity

Instead we believe macro-level variables related to crime should be estimated in terms of

the number of patrol officers in a patrol area specifically violent crimes per officer and property

crimes per officer For instance some officers may patrol a lower crime area but end up

responding to a greater number of violent crimes than officers in a high crime area simply

because they have fewer officers working the street This ldquocrime per coprdquo ratio can dramatically

affect officersrsquo productivity

For example when an officer investigates a crime he or she might interview the victim

suspect and witnesses as well as take photographs collect evidence and make an arrest There

may be additional follow-up the next day or week such as checking pawnshops for stolen

property or tracking down and interviewing additional witnesses All these activities could

decrease an officerrsquos time for self-initiated activities and in turn an officerrsquos overall

productivity A high crime per cop ratio therefore could decrease productivity for officers even

if these officers work in an area with a low crime rate Furthermore an arearsquos crime per cop

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

7252019 PIJPSM-05-2015-0064

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

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10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

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officers Married officers have someone in whom to confide a partner who hears about the

challenges and rigors of the job which may lead to stress reduction and improve workplace

motivation An officerrsquos age is another consideration Older officers might be less productive

than younger officers perhaps due to burnout as well as the physical demands of law

enforcement (Goodman 1990) Officersrsquo perceptions of their job may also affect their

proactivity and in turn productivity Brehm and Gates (1993) found that officers who disliked

certain aspects of law enforcement (eg taking people to jail) impacted whether officers engaged

in proactive activities or shirked their duties

Additionally there are also operational features (the ldquoday to dayrdquo rigors) of law

enforcement which can decrease productivity and increase misconduct such as the perceived

danger of the job (Amaranto et al 2003) work schedules and shift work (Vila Morrison amp

Kenney 2002) and fatigue (Vila amp Kenney 2002) Notably in studying the relationship

between daily work experience and performance Shane (2011) found that workload was the

ldquomost important predictor of performancerdquo (p 13)

We believe this last finding merits further study First supervisors evaluate patrol

officers at least in part using productivity outputs If there are factors (ie heavy workload)

beyond an officerrsquos control that are affecting his or her productivity both line-level supervisors

and command staff members should acknowledge and account for these variables during

performance reviews Second if macro-level variables create different workloads thereby

affecting productivity outputs then police researchers should include these measures in future

studies on police activity We suggest that there are at least two macro-level variables important

to future police productivity research

Crime-to-Cop Ratios and Patrol Officer Productivity

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Criminological research has long recognized that crime rates are not uniform across

neighborhoods and cities (Sherman et al 1989 Weisburd et al 1993) Instead of ldquopolicing

peoplerdquo law enforcement agencies frequently identify ldquohot spotsrdquo and devote additional

resources to reducing crime and disorder in specific problem areas With this perspective in

mind it might seem natural to examine the relationship between the crime rate of a patrol area

and an officerrsquos productivity outputs (or vice-versa) For example a high crime area might net

an officer more arrests (and therefore more productivity outputs) than a low crime area On the

other hand a high crime area might also occupy a great deal of an officerrsquos productive time

prohibiting the officer from engaging in proactive activities However crime rate does not fully

capture how a particular area might affect an officerrsquos productivity

Instead we believe macro-level variables related to crime should be estimated in terms of

the number of patrol officers in a patrol area specifically violent crimes per officer and property

crimes per officer For instance some officers may patrol a lower crime area but end up

responding to a greater number of violent crimes than officers in a high crime area simply

because they have fewer officers working the street This ldquocrime per coprdquo ratio can dramatically

affect officersrsquo productivity

For example when an officer investigates a crime he or she might interview the victim

suspect and witnesses as well as take photographs collect evidence and make an arrest There

may be additional follow-up the next day or week such as checking pawnshops for stolen

property or tracking down and interviewing additional witnesses All these activities could

decrease an officerrsquos time for self-initiated activities and in turn an officerrsquos overall

productivity A high crime per cop ratio therefore could decrease productivity for officers even

if these officers work in an area with a low crime rate Furthermore an arearsquos crime per cop

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

7252019 PIJPSM-05-2015-0064

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

7252019 PIJPSM-05-2015-0064

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

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httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

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C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 6: PIJPSM-05-2015-0064

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Criminological research has long recognized that crime rates are not uniform across

neighborhoods and cities (Sherman et al 1989 Weisburd et al 1993) Instead of ldquopolicing

peoplerdquo law enforcement agencies frequently identify ldquohot spotsrdquo and devote additional

resources to reducing crime and disorder in specific problem areas With this perspective in

mind it might seem natural to examine the relationship between the crime rate of a patrol area

and an officerrsquos productivity outputs (or vice-versa) For example a high crime area might net

an officer more arrests (and therefore more productivity outputs) than a low crime area On the

other hand a high crime area might also occupy a great deal of an officerrsquos productive time

prohibiting the officer from engaging in proactive activities However crime rate does not fully

capture how a particular area might affect an officerrsquos productivity

Instead we believe macro-level variables related to crime should be estimated in terms of

the number of patrol officers in a patrol area specifically violent crimes per officer and property

crimes per officer For instance some officers may patrol a lower crime area but end up

responding to a greater number of violent crimes than officers in a high crime area simply

because they have fewer officers working the street This ldquocrime per coprdquo ratio can dramatically

affect officersrsquo productivity

For example when an officer investigates a crime he or she might interview the victim

suspect and witnesses as well as take photographs collect evidence and make an arrest There

may be additional follow-up the next day or week such as checking pawnshops for stolen

property or tracking down and interviewing additional witnesses All these activities could

decrease an officerrsquos time for self-initiated activities and in turn an officerrsquos overall

productivity A high crime per cop ratio therefore could decrease productivity for officers even

if these officers work in an area with a low crime rate Furthermore an arearsquos crime per cop

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 7: PIJPSM-05-2015-0064

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ratio could also affect officersrsquo productive time even if they are not the primary investigating

officer because secondary officers are often needed during serious incidents such as robberies or

burglaries

The ldquoload sheddingrdquo hypothesis by Maxfield et al (1980 see also Maxfield 1982) also

has important implications for any study examining patrol officer productivity Maxfield et al

suggested that while variations in workload do not affect patrol officersrsquo decisions to record

serious crimes workload does affect officersrsquo decisions to record less serious crimes it may also

affect self-initiated activities as well (Herbert 1989)

Finally we believe that macro-level variables affecting productivity should be divided

between violent and property crimes to account for the time and resources needed to investigate

each incident type When officers respond to assaults they often contact suspects and victims on

scene meaning that officers are able to interview all involved individuals collect evidence and

make an arrest sometimes in less than an hour However when officers respond to burglaries or

larcenies they may be required to dust for fingerprints swab for DNA canvass a neighborhood

for witnesses check pawnshops and engage in other investigative activities that require hours

and even days if the case requires follow-up

With these issues in mind our study addresses the following research questions First

what is the relationship between a patrol arearsquos rate of violent crimes per officer and patrol

officer productivity outputs (ie traffic citations as well as warrant misdemeanor and felony

arrests) Second what is the relationship between a patrol arearsquos rate of property crimes per

officer and patrol officer productivity outputs (again traffic citations and warrant misdemeanor

and felony arrests) Third what is the relationship between the rate of property and violent

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

7252019 PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

7252019 PIJPSM-05-2015-0064

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

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983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

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983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

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crimes per officer and a patrol officerrsquos productivity when we introduce a more sophisticated

method for analyzing productivity a metric based on productive time and not total time on duty

Before discussing our data and methods there are two important issues meriting brief

discussion First we argue that the crime-to-cop ratio may affect the number of traffic stops

warrants misdemeanors and felonies that a patrol officer makes It can also be argued that the

number of arrests might impact the crime-to-cop ratio Our intent is not to comprehensively

discuss the relationship between the number of officersofficer arrests and an arearsquos crime rate

but it bears noting that the research is inconclusive on this point

Some evidence suggests that the relationship between arrests and crime rates is non-

linear that is crime rates decrease as arrests increase but eventually hit a ldquofloorrdquo and reach

equilibrium (Kane 2006) Second when studies examine the arrest-crime rate relationship they

often find that the relationship only exists for specific crimes in their datasets such as robbery

and motor vehicle thefts (Corman Hope amp Mocan 2005) robbery but not assaults (Kane 2006)

and homicide and auto thefts only (Cloninger amp Sartorius 1979) and so forth Overall the

literature on the arrests-crime rate relationship is mixedmdashsome research finds an effect between

arrests and crime rates some does not (Huizinga and Henry 2008)

The second issue concerns whether a law enforcement agency operates using a generalist

or specialist policing style We analyze data from a generalist municipal police department

meaning that patrol officers investigate low and mid-level crimes but investigators and

detectives are responsible for handling serious crimes cases involving lengthy investigations

(eg narcotics trafficking or white-collar crimes) and incidents in which patrol officers may

need assistance (for example an incident involving numerous victims and witnesses as well as

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

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983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

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cases involving extensive follow-up or knowledge on a specific subject such as gangs or

narcotics)

By contrast when patrol officers in a specialist-style police department respond to any

incident potentially requiring follow-up they might only contact the victim and either hold the

scene until an investigator arrives or forward the information to a detective for follow-up It is

possible indeed likely that macro-level variables might affect generalist patrol officers

differently than specialized officers Due to data limitations however our study focuses on

generalist police officers

Data and Methods

We gathered data on patrol officers and their patrol areas from several sources First we

collected patrol officer productivity data from the Lincoln (Nebraska) Police Departmentrsquos 2013-

2014 productivity reports Using Computer-Aided Dispatch (CAD) and a centralized

productivity database LPD measures numerous patrol officer activities Every month (and

year) LPD generates productivity reports which display each patrol officerrsquos activities and

outputs (see Table 1 for an example of a squadrsquos annual productivity report) Each patrol

activity and output merits further explanation

INSERT TABLE 1 HERE

Calls for Service (CFS) and Officer Assist time When dispatchers send patrol officers on

a call they use CAD to track the minutes the officer spends on the call If the call is a priority

incident dispatchers send both a primary and secondary officer Other unassigned officers might

also respond to the CFS meaning that multiple officers could be secondary officers The annual

productivity record tracks amount of time an officer spent as a primary responder and a

secondary responder

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

7252019 PIJPSM-05-2015-0064

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

7252019 PIJPSM-05-2015-0064

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

7252019 PIJPSM-05-2015-0064

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 10: PIJPSM-05-2015-0064

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Report writing time Standard operating procedures dictate that LPD patrol officers

complete specific types of reports for incidents An incident report (IR) details biographical

information of the individuals involved in the incident and summarizes the incident An

Additional Case Information (ACI) is a more detailed report that documents additional

investigative steps or the actions of assisting officers Although the time spent on an IR or ACI

could vary depending on the call for service the average IR and ACI take roughly twenty

minutes to complete1

The Lincoln Police Department also tracks self-initiated activities Most productivity

results from the following proactive activities

Selectives The Lincoln Police Department tracks specific officer patrol activity by

coding its neighborhoods schools parks and business districts When an officer patrols an at-

risk business district or a high-crime neighborhood for example the officer notifies dispatch

using that arearsquos specific code Girded by the principles of ldquohot spotsrdquo policing research officers

use selectives to identify potential candidates for POP projects and heighten the perception of

risk among criminals (Braga amp Bond 2008)

Traffic Warnings and Official Citations Every Lincoln patrol officer drives a police

cruiser and conducts traffic enforcement issuing traffic warnings and official citations The

LPD records department tracks patrol officersrsquo warnings and citations

Misdemeanors felonies and warrants Patrol officers also make misdemeanor and

felony arrests during their productive time Officers might detain a motorist and arrest him or

her for driving under a suspended license or driving while intoxicated or contact a pedestrian

1 983119983142983142983145983139983141983154983155 983156983161983152983141 983137983148983148 983154983141983152983151983154983156983155 983151983150 983139983151983149983152983157983156983141983154983155 983127983141 983151983138983156983137983145983150983141983140 983156983144983145983155 983137983158983141983154983137983143983141 983138983161 983151983138983155983141983154983158983145983150983143 983137 983155983137983149983152983148983141 983151983142 983116983145983150983139983151983148983150 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

983139983151983149983152983148983141983156983145983150983143 983113983122983155 983137983150983140 983105983107983113983155 983137983150983140 983159983141 983154983141983139983151983143983150983145983162983141 983156983144983137983156 983156983144983145983155 983137983158983141983154983137983143983141 983149983137983161 983140983145983142983142983141983154 983142983154983151983149 983151983156983144983141983154 983152983151983148983145983139983141 983140983141983152983137983154983156983149983141983150983156983155 983117983151983154983141983151983158983141983154983145983142 983140983141983152983137983154983156983149983141983150983156983155 983154983141983153983157983145983154983141 983151983142983142983145983139983141983154983155 983156983151 983139983151983149983152983148983141983156983141 983156983144983141983145983154 983154983141983152983151983154983156983155 983138983141983142983151983154983141 983138983141983139983151983149983145983150983143 983137983158983137983145983148983137983138983148983141 983142983151983154 983137983150983151983156983144983141983154 983139983137983148983148 983142983151983154 983155983141983154983158983145983139983141

983156983144983145983155 983149983141983137983155983157983154983141983149983141983150983156 983145983155 983157983150983150983141983139983141983155983155983137983154983161

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

7252019 PIJPSM-05-2015-0064

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

7252019 PIJPSM-05-2015-0064

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

7252019 PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

7252019 PIJPSM-05-2015-0064

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

7252019 PIJPSM-05-2015-0064

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

7252019 PIJPSM-05-2015-0064

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

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983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

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983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

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983117983137983148983141 4673 1622 366 147 1613 1051 91 158

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983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

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983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

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983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

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983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 11: PIJPSM-05-2015-0064

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and make an arrest for a sex offender registration violation Officers can also search their

departmentrsquos electronic database for individuals with outstanding warrants in their patrol areas

and attempt to arrest these offenders As with warnings and citations the LPD records

department documents and tracks misdemeanor felony and warrant arrests Moreover the court

system also monitors these types of outputs to process cases thereby adding an additional layer

of reporting accuracy and reliability

Field information reports We also measured the number of field information or

ldquointelligencerdquo reports Officers complete these internal reports to document suspicious or

dangerous individuals or circumstances though these reports are not publicly available

VORC In addition to the raw outputs of traffic citations warrants misdemeanors and

felonies we also include an advanced metric for measuring a patrol officerrsquos productivity Value

Over Replacement Cop (VORC) is a method for evaluating officers that assigns different

weights to productivity outputs and then assesses officer productivity in terms of available time

for self-initiated activities or productive time (Bonkiewicz 2015) We use a variation of this

formula that multiplies an officerrsquos officials misdemeanors and felonies by his or her

prosecution rate Our modified use of VORC can best be explained using the following figure

(Figure 1) and five-step process

INSERT FIGURE 1 HERE

where = total monthly on-duty minutes = CFS minutes Γ = follow-up time and meetings ∆

= officer assist time Ε = of IRs Ζ = of ACIs M = of intelligence reports Η = of

selectives Θ = of warnings times two Κ = of warrants times three Ι = of officials times

three Λ = of misdemeanor arrests times their respective weights Ν = of felonies types their

respective weights Ρ = an officerrsquos prosecution rate Ξ = Officerrsquos Productive time (Α-(Β+Γ+∆+

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

7252019 PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

7252019 PIJPSM-05-2015-0064

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

1 88 22812 5208 6132 216 348 396 396 264 60 24 72 7

2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

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983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

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983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

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983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

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983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

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983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

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983117983137983148983141 4673 1622 366 147 1613 1051 91 158

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983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

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7252019 PIJPSM-05-2015-0064

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983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

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983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

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983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

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983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

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983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 12: PIJPSM-05-2015-0064

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20(Ε+Ζ))) Ο= Department average P-score or average (Η+ ((Θ)+(Ι)+(Κ)+(Λ)+(Μ)+(Ν)Ρ))

and Π = Department average Self-Initiated Time

First VORC calculates an officerrsquos total minutes spent on CFS follow-ups officer

assists and reports This amount is an officerrsquos total work time or service minutes Second the

formula subtracts an officerrsquos service minutes from the total on-duty minutes2 This is the

officerrsquos amount of productive time Third VORC calculates an officerrsquos productivity score (or

P-score) using a weighted index Departments can choose different weights for productivity

outputs but for the purpose of this study we used our weights based on the statutes governing

the Lincoln Police Department Citations and arrests are weighted based on whether the offense

was a Traffic Offense a Class III II or I Misdemeanor or a Class V IV III II or I Felony

Accordingly a patrol selective is worth one point a traffic warning two points a traffic citation

three points a warrant arrest three points a Class III misdemeanor arrest four points a Class II

misdemeanor arrest five points a Class I misdemeanor arrest six points a Class V Felony seven

points a Class IV Felony eight points a Class III Felony nine points and Class II and I Felonies

(eg homicides) ten points3 The sum of the weighted productivity outputs is the officerrsquos P-

score The P-score is divided by amount of productive time and then multiplied by 100 (for ease

of understanding) This value the productivity quotient represents the officerrsquos productivity

given the available minutes for proactivity such as searching for wanted individuals or traffic

enforcement

Fourth VORC creates a hypothetical replacement officer against which to measure the

patrol officerrsquos output This replacement player might be imagined as a rookie patrol officer or

983090 983119983150983085983140983157983156983161 983156983145983149983141 983140983151983141983155 983150983151983156 983145983150983139983148983157983140983141 983156983154983137983145983150983145983150983143 983156983145983149983141 983158983137983139983137983156983145983151983150 983151983154 983144983151983148983145983140983137983161 983140983137983161983155 983151983142983142 983151983154 983155983145983139983147 983148983141983137983158983141 983113983150 983151983156983144983141983154 983159983151983154983140983155 983151983150983085983140983157983156983161

983156983145983149983141 983145983155 983156983144983141 983137983149983151983157983150983156 983151983142 983156983145983149983141 983137 983152983137983156983154983151983148 983151983142983142983145983139983141983154 983155983152983141983150983156 983159983151983154983147983145983150983143 983156983144983141 983155983156983154983141983141983156983091 983119983157983154 983159983141983145983143983144983156983145983150983143 983155983161983155983156983141983149 983145983155 983151983150983148983161 983151983150983141 983141983160983137983149983152983148983141 983151983142 983156983144983141 983142983148983141983160983145983138983145983148983145983156983161 983156983144983137983156 983126983119983122983107 983151983142983142983141983154983155 983140983141983152983137983154983156983149983141983150983156983155983099 983141983137983139983144 983137983143983141983150983139983161 983139983137983150

983152983154983145983151983154983145983156983145983162983141 983137983150983140 983137983155983155983145983143983150 983139983151983154983154983141983155983152983151983150983140983145983150983143 983159983141983145983143983144983156983155 983156983151 983156983144983141983145983154 983152983154983141983142983141983154983154983141983140 983152983154983151983140983157983139983156983145983158983145983156983161 983151983157983156983152983157983156983155

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

7252019 PIJPSM-05-2015-0064

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

7252019 PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

7252019 PIJPSM-05-2015-0064

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

7252019 PIJPSM-05-2015-0064

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

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983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

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983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

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983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

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983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

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a recruit who has not completed the academy performing at ninety percent the capacity of fully

trained police officer4 Using LPDrsquos data VORC creates a hypothetical replacement officer by

dividing the departmental average P-score by the departmental average for productive time and

then multiplying it by the officerrsquos productive time to determine what an average officer would

have generated given the officerrsquos amount of productive time This figure is then multiplied by

9 (the capacity of a replacement officer) divided by the officerrsquos productive time and then

multiplied by 100 to generate the replacement officerrsquos productivity quotient Finally VORC

subtracts the replacement officerrsquos score from the patrol officerrsquos score to calculate the officerrsquos

value over the replacement officer This number or VORC indicates the officerrsquos productivity

per time for self-initiated activities compared to the replacement officerrsquos productivity For

example a VORC of 12 means than officer would produce 012 more productivity points (some

combination of warnings citations and arrests) per minute than a replacement officer

Biographical variables We gathered biographical information about the officers in the

sample including gender years of LPD experience maritalcohabiting status and number of

children We also controlled for whether the officer worked first second or third shift because

our data showed significant differences in the number of calls for service each shift handled as

well as the number of reports each shift completed

Geographic variables It is necessary to measure the characteristics of patrol areas to

account for variation across patrol areas For example some areas may feature different crime

rates or levels of social disorganization which command more department resources and police

officers We gathered data by first mapping out every squadrsquos patrol area and then obtaining

tract-level data from the 2010 US Census Our models included measures of established of

983092

983123983139983144983151983148983137983154983155 983137983150983140 983152983151983148983145983139983161 983149983137983147983141983154983155 983149983137983161 983140983145983155983137983143983154983141983141 983159983145983156983144 983141983155983156983145983149983137983156983145983150983143 983137 983154983141983152983148983137983139983141983149983141983150983156 983151983142983142983145983139983141983154991257983155 983139983137983152983137983139983145983156983161 983137983156 983150983145983150983141983156983161 983152983141983154983139983141983150983156 983119983157983154983143983151983137983148 983145983155 983150983151983156 983156983151 983140983141983142983145983150983145983156983145983158983141983148983161 983141983155983156983145983149983137983156983141 983137 983144983161983152983151983156983144983141983156983145983139983137983148 983151983142983142983145983139983141983154991257983155 983152983154983151983140983157983139983156983145983158983145983156983161 983138983157983156 983149983141983154983141983148983161 983156983151 983141983155983156983137983138983148983145983155983144 983137 983154983141983137983155983151983150983137983138983148983141 983142983145983160983141983140

983152983151983145983150983156 983137983143983137983145983150983155983156 983159983144983145983139983144 983156983151 983139983151983149983152983137983154983141 983137983148983148 983152983137983156983154983151983148 983151983142983142983145983139983141983154983155

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

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10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

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983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

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983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

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983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

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983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

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C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

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983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

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correlates of crime including population density (Hipp amp Roussell 2013) household income

(Gould Weinberg and Mustard 2002) and racial composition (Light amp Harris 2012)

Specifically we use each arearsquos population density median household income and percent

white We also included measures for each arearsquos violent and property crime rate Finally we

gathered information about the number of violent crimes (murders assaults aggravated assaults

sexual assaults and robberies) property crimes (larcenies burglaries vandalisms frauds

forgeries and motor vehicle thefts) and number of police officers in each patrol area thereby

creating variables for violent crime per officer and property crime per officer

Since LPDrsquos patrol officers are grouped with squads it is reasonable to believe that an

officerrsquos productivity might be more similar to an officer within their squad compared to an

officer in a different squad To account for the potential correlations between the individual

units as well as the multi-level nature of the data we used hierarchical linear modeling to

analyze the data

Our primary level variables include an officerrsquos gender marital status number of

children years of law enforcement experience shift calls for service annual number of traffic

stops and citations field information reports and misdemeanor felony and warrant arrests We

also used the officersrsquo productivity information to calculate each patrol officerrsquos VORC

Our secondary level variables include the violent crime per officer rate and property

crime per officer rate for the patrol area of each squad as well several control variables

including population density household median income percent white and the patrol arearsquos

violent and property crime rate Table 2 displays the summary statistics for the first and second-

level variables

INSERT TABLE 2 HERE

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

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983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 15: PIJPSM-05-2015-0064

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Results

We hypothesized that the violent and property crime-to-cop ratios of an area might affect

the raw productivity outputs of patrol officers as well as a more advanced productivity metric

To examine these questions we constructed five hierarchical linear models estimating the

correlations between reported violent and property crimes per officer and a patrol officerrsquos

annual traffic citations warrant misdemeanor felony arrests and Value Over Replacement Cop

Although not presented here we estimated null models for all dependent variables and found that

significant variation existed between squads when we included no variables included in the

models The chi-square for the LR test for all five null models was statistically significant (p lt

000 in all models)

Table 3 shows that a rise in reported violent crimes per officer increases an officerrsquos

number of warrants and misdemeanors (b= 29 and 76) while arise in reported property crimes

per officer decreases an officerrsquos number of warrants and misdemeanors (b= -15 and -52) We

found no relationship between the crime-to-cop ratios and felony arrests However both the

rates of violent and property crimes per officer decreased the number of traffic citations an

officer writes (b= -168 and -225)

Insert Table 3 here

Table 3 also shows that traffic stops and field information reports are positively

associated with warrant and misdemeanor arrests This supports what police practitioners

already suspect the cops with the most arrests are extremely proactive patrol officers who stop a

large number of vehicles and build investigations through the use of field contacts and

information reports For instance an officer can build felony narcotics cases by contacting

7252019 PIJPSM-05-2015-0064

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

7252019 PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

7252019 PIJPSM-05-2015-0064

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

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5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

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983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

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suspects and informants in the field documenting these efforts through field information reports

and eventually using this information to write search warrants and conduct drug interdiction

Next we investigated whether this relationship between the crime-to-cop ratios and

productivity outputs exists when using an advanced productivity metric specifically an officerrsquos

Value Over Replacement Cop (VORC)

INSERT TABLE 4 HERE

Table 4 shows that there is no correlation between the ratio of property and violent

crimes per officer and VORC Although this stands in contrast to our earlier results we would

not expect to find a relationship between these variables and VORC Advanced metrics such as

VORC evaluate officers based on the amount of time for self-initiated activities (productive

time) and not raw productivity outputs like misdemeanor or felony arrests Even if an officer

took an extremely large number of property crimes thereby decreasing their productive time

VORC would only evaluate that officer based on what the officer produced with the small

amount of productive time This suggests that while a teamrsquos crime-to-cop ratio could affect an

officerrsquos raw productivity outputs ie arrests a teamrsquos crime-to-cop ratio would not affect an

officerrsquos VORC

For example during a given month an officer may take an unusually large number of

burglaries or larcenies thereby leaving the officer with only ten hours for self-initiated activities

With this reduced amount of productive time the officer may generate a below-average number

of officials warrants misdemeanors and felonies which in turn may lead a supervisor to

potentially downgrade the officerrsquos productivity However VORC would recognize and account

for the high number of calls for service minutes and analyze the officerrsquos productivity based on

what the officer generated with only ten hours of productive time It may be that the officer was

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

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983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 17: PIJPSM-05-2015-0064

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actually very productive but they simply didnrsquot have enough productive time to generate the

same number of traffic citations and arrests as an officer who responded to far fewer property

crimes

Table 4 also shows that traffic stops and field intelligence reports are positively

correlated with VORC These results are consistent with the principles of how VORC evaluates

patrol officer productivity and provides additional support for the validity of this advanced

metric VORC accounts for numerous variables that affect productive time (ie calls for service

minutes) meaning that the key factors which increase or decrease an officerrsquos VORC are largely

related to self-initiated activities (ie traffic stops and information reports) VORC therefore

accounts for the potential effects of macro-level variables and analyzes the activities of the

officer during his or her productive time Nonetheless we recognize that because traffic stops

and field information reports are correlated with VORC an arearsquos crime-to-cop ratio might still

affect an officerrsquos VORC indirectly by impacting the number of stops and information reports

they generate

Discussion

There are several factors which affect a patrol officerrsquos productivity including

biographical characteristics officersrsquo perceptions and attitudes and organizational and

operational features among others This paper identified two macro-level variablesmdashproperty

crimes per officer and violent crimes per officermdashwhich affect the number of traffic citations

warrants misdemeanors and felonies generated annually by an officer Using data from a mid-

sized police department we found that a patrol areas rate of property crimes per officer was

associated with a moderate decrease in an officers annual number of traffic citations warrant

arrests and misdemeanor arrests while a patrol areas rate of violent crimes per officer was also

7252019 PIJPSM-05-2015-0064

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

7252019 PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

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httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

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983152lt001

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

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983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

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C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 18: PIJPSM-05-2015-0064

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associated with a moderate decrease in an officers annual number of traffic citations We also

found that a patrol areas rate of violent crimes per officer is associated with a moderate increase

in an officers annual number of warrant and misdemeanor arrests However when we used a

more advanced productivity metric we found no relationship between property and violent

crimes per officer and an officerrsquos Value Over Replacement Cop or VORC

There are several factors which explain the differing effects of the crime-to-cop ratios on

productivity outputs Let us first address why the violent crime-to-cop ratio would increase a

patrol officerrsquos warrants and misdemeanors while the property crime-to-cop ratio would decrease

these outputs Notably half of all victims of violent crimes know the offender (Truman amp Rand

2010) which aids law enforcement in identifying and locating the perpetrator Moreover both

suspect and victim are frequently on scene when police officers arrive such as during domestic

disturbances Being able to identify and locate the perpetrator helps patrol officers make arrests

thereby increasing their misdemeanor and felony arrests in violent crimes Additionally when

patrol officers arrive and contact individuals during an incident it is standard procedure to check

if the parties involved have outstanding warrants This means that the greater number of violent

crimes that officers respond to the more chances they have to arrest individuals who might have

outstanding warrants It makes sense then that officers who respond to a greater number of

violent crimes have more chances to make warrant and misdemeanor arrests

Conversely property crimes may supply the officer with fewer warrant and misdemeanor

arrests because of low clearance rates We examined the difference in clearance rates between

property and violent crime using incident data from the Lincoln Police Department and we

found that the clearance rate for violent crimes was 418 compared to only 237 for property

crimes Moreover property crimes often also require more investigative time than violent

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

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983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 19: PIJPSM-05-2015-0064

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crimes Property crime investigations often require considerable follow-up by officers such as

processing a scene contacting financial institutions and checking pawnshops for stolen property

In general property crimes are more time-intensive than violent crimes thereby decreasing

productive time and opportunities for proactive activities while simultaneously netting officers

fewer arrests because of low clearance rates

The impact of a teamrsquos crime-to-cop ratio can also be seen in the relationship between

property and violent crime per officer and the number of traffic citations Table 3 shows that a

rise in both reported violent and property crimes per officer decrease an officerrsquos number of

traffic citations Quite simply if officers respond to a high number of property and violent

crimes then they will have fewer minutes to conduct traffic enforcement and other proactive

enforcement

As noted it is possible that the correlation is bi-directional If an officer makes a greater

number of arrests then a team may witness a decrease in crime because prolific criminals may

have been arrested and placed in jail For example one might interpret Table 3 to mean that an

increase in warrant and misdemeanor warrants led to a decrease in the number of property crimes

per officer However under this hypothesis we should also see that an increase in warrant and

misdemeanor arrests leads to a decrease in the number of violent crimes per officer Instead we

see the opposite hypothesized effect ie more arrests leading to more reported violent crimes 5

983093 983127983141 983139983151983150983155983156983154983157983139983156983141983140 983154983141983143983154983141983155983155983145983151983150 983149983151983140983141983148983155 983157983155983145983150983143 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983142983154983151983149

983156983144983141 983152983154983141983139983141983140983145983150983143 983149983151983150983156983144 983156983151 983152983154983141983140983145983139983156 983138983151983156983144 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983142983151983154 983156983144983141 983149983151983150983156983144983155 983145983150 983151983157983154 983140983137983156983137983155983141983156 983127983141 983142983151983157983150983140 983150983151

983155983156983137983156983145983155983156983145983139983137983148983148983161 983155983145983143983150983145983142983145983139983137983150983156 983154983141983148983137983156983145983151983150983155983144983145983152983155 983138983141983156983159983141983141983150 983139983145983156983137983156983145983151983150983155 983159983137983154983154983137983150983156 983137983154983154983141983155983156983155 983149983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155

983137983150983140 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141983155 983151983142 983156983144983141 983138983141983137983156983155 983112983151983159983141983158983141983154 983137983142983156983141983154 983140983145983155983137983143983143983154983141983143983137983156983145983150983143 983156983144983141 983158983145983151983148983141983150983156 983137983150983140 983152983154983151983152983141983154983156983161

983139983154983145983149983141 983154983137983156983141983155 983145983150983156983151 983155983152983141983139983145983142983145983139 983139983154983145983149983141983155 983159983141 983140983145983140 983142983145983150983140 983156983144983137983156 983149983145983155983140983141983149983141983137983150983151983154 983137983150983140 983142983141983148983151983150983161 983137983154983154983141983155983156983155 983155983145983143983150983145983142983145983139983137983150983156983148983161 983152983154983141983140983145983139983156983141983140 983137 983140983141983139983154983141983137983155983141

983145983150 983154983151983138983138983141983154983161 983154983137983156983141983155 983159983144983145983139983144 983145983155 983139983151983150983155983145983155983156983141983150983156 983159983145983156983144 983156983144983141 983148983145983156983141983154983137983156983157983154983141 983105983140983140983145983156983145983151983150983137983148983148983161 983159983141 983145983150983156983141983154983158983145983141983159983141983140 983140983141983152983137983154983156983149983141983150983156 983152983141983154983155983151983150983150983141983148 983137983150983140983148983141983137983154983150983141983140 983156983144983137983156 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 983108983141983152983137983154983156983149983141983150983156 983144983137983140 983155983156983137983142983142983141983140 983137 983156983141983137983149 983140983141983155983145983143983150983141983140 983155983152983141983139983145983142983145983139983137983148983148983161 983156983151 983137983152983152983154983141983144983141983150983140 983154983151983138983138983141983154983161

983155983157983155983152983141983139983156983155 983140983157983154983145983150983143 983156983144983145983155 983156983145983149983141983142983154983137983149983141 983159983144983145983139983144 983155983141983141983149983155 983156983151 983141983160983152983148983137983145983150 983156983144983141 983137983154983154983141983155983156983085983154983151983138983138983141983154983161 983154983137983156983141 983154983141983148983137983156983145983151983150983155983144983145983152

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

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7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

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983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

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983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

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983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

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983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

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983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 20: PIJPSM-05-2015-0064

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We believe our explanation has a stronger theoretical foundation The ratio of property

crimes per officer affects productivity outputs differently than the ratio of violent crimes per

officer for two reasons First violent crimes are different in nature than property crimes

especially with regard to clearance rates Second property crimes often require more

investigative and follow-up time than violent crimes thereby reducing an officerrsquos amount of

productive time and proactive activity

Table 3 also provides a key piece of evidence to support this assertion Table 3 shows

that the number of reported violent crimes per officer increases an officerrsquos number of warrant

and misdemeanor arrests Yet the relationship is the opposite for traffic enforcement the violent

crime-to-cop ratio actually decreases traffic citations This change is due to the fact that while

violent crime investigations often yield warrant and misdemeanor arrests they do not produce

traffic citations Furthermore responding to a greater number of violent crimes decreases the

amount of available time to conduct traffic enforcement in turn reducing the number of traffic

citations In other words the violent crime-to-cop ratio affects traffic stops the same way that

the property crime-to-cop ratio affects all productivity outputs by reducing an officerrsquos

productive time and opportunities for proactivity In fact we found a moderate correlation

between a patrol arearsquos crime-to-cop ratio and the amount of productive time enjoyed by officers

who worked that area The correlation between an arearsquos violent crime-to-cop ratio and

productive time was -21 while the correlation between an arearsquos property crime-to-cop ratio and

productive time was -33 We believe this evidence indicates that officers who work in areas

with a high crime-to-cop ratio have less time for self-initiated activities which drives down

productivity

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 21: PIJPSM-05-2015-0064

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We suggest that the number of police officers and crime rates of an area need to be

analyzed in conjunction with each other Prior theories of police productivity have viewed and

examined these variables separately when in reality we should view these variables in tandem

Combining these variables into crime-to-cop ratios provides a more nuancedmdashand accuratemdash

understanding of patrol activities and their relationship to productivity

Although we found strong evidence that an officerrsquos patrol area affects his or her

productivity (in terms of raw outputs) we also found that a few officer-level variables affected

productivity as well including traffic stops intelligence reports and working third shift Our

results appear to substantiate what many police practitioners already suspect officers who are

proactive in contacting citizens (traffic stops) and building investigations (intelligence reports)

generate more warrant and misdemeanor arrests In addition while some newer police officers

are forced to work third shift because they do not have sufficient seniority to bid for better days

off and shift times many officers work nights because they enjoy the types of calls (eg in-

progress felonies) meaning they may be more motivated to stop vehicles make field contacts

and in turn engage in activities that generate arrests (Brehm amp Gates 1993)

These results have important implications for police researchers and administrators

First our results suggest a need for a deeper understanding of how the staffing levels crime

rates and the other characteristics of a patrol area intersect Second if departments evaluate

their patrol officers using raw productivity outputs such as misdemeanor or felony arrests

administrators must recognize that factors beyond the control of patrol officers might affect

monthly or annual productivity Our research suggests that a patrol arearsquos crime-to-cop ratio can

substantially affect a patrol officerrsquos productivity regardless of the actual crime rate If the

characteristics of a patrol area affect raw productivity outputs police departments should employ

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

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983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

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983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 22: PIJPSM-05-2015-0064

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more advanced productivity analytics (ie VORC) that account for activities which reduce

productive time and evaluate an officerrsquos productivity in terms of available minutes for

proactivity

Nonetheless evaluating both patrol officers and police departments using traffic citations

warrants misdemeanors and felonies is useful because this type of data is readily understood by

citizens and civic officials A neighborhood watch group for instance might care more about

the number of arrests their officers make and less about those officersrsquo productivity scores Our

data suggests that if citizens want patrol officers to write more traffic citations and make more

arrests they should lobby for more police officers on the street It is true that reducing an arearsquos

crime rate impacts the crime-to-cop ratio but our results indicate that putting police officers on

the street may be the most direct way to affect the crime-to-cop ratio

Our study is not without limitations We only examined a police department which uses

the generalist style of policing and it is unknown if our results are applicable to police

departments which use a specialist style of policing Theoretically a departmentrsquos policing

styles can affect factors that increase or decrease a patrol officerrsquos productive time It is possible

that the number of property crimes and violent crimes per officer do not significantly affect a

specialist patrol officerrsquos productivity outputs versus a generalist officerrsquos outputs Future

studies should investigate whether our results can be generalized to all police departments

We have only identified two macro-level variables which affect patrol officer

productivity and we recognize there may be other variables In addition we recommend that

future studies incorporate a wider array of variables and test competing models to determine

whether micro or macro-level variables exhibit stronger effects on productivity In the end

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

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References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

1 88 22812 5208 6132 216 348 396 396 264 60 24 72 7

2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 23: PIJPSM-05-2015-0064

7252019 PIJPSM-05-2015-0064

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managing patrol officers and improving productivity requires a greater understanding of both

patrol officers and the areas they work

Acknowledgements and Credits We would like to thank Denver Police Department Crime

Analyst Melissa Ohlhorst and Pennsylvania State University Professor Barry Ruback as well as

the three anonymous reviewers for their insightful comments We also salute Lincoln Police

Sergeant Jake Dilsaver for his logistical support of this project

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2430

References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

1 88 22812 5208 6132 216 348 396 396 264 60 24 72 7

2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 24: PIJPSM-05-2015-0064

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2430

References

Amaranto E Steinberg J Castellano C and Mitchell R (2003) ldquoPolice stress interventionsrdquo

Brief Treatment and Crisis Intervention Vol 3 No 1 pp 47-53

Becker G (1985) ldquoHuman capital effort and the sexual division of laborrdquo The Journal of

Labor EconomicsVol 3 No 1 pp 33-58

Bonkiewicz L (2015) ldquoBobbies and baseball players Evaluating patrol officer productivity

using sabermetricsrdquo Police Quarterly Vol 18 No 1 pp 55-78

Braga A and Bond J (2008) ldquoPolicing crime and disorder hot spots A randomized controlled

trialrdquo Criminology Vol 46 No 3 pp 577-607

Brown J and Campbell E (1990) ldquoSources of occupational stress in the policerdquo Work

and Stress Vol 4 No 4 pp 305-318

Chappell A MacDonald J and Manz P (2006) ldquoThe organizational determinants

of police arrest decisionsrdquo Crime and Delinquency Vol 52 No 2 pp 287-306

Cloninger D and Sartorius L (1979) ldquoCrime rates clearance rates and enforcement effort

The case of Houston Texasrdquo American Journal of Economics and Sociology Vol 38

No 4 pp 389-402

Corman H and Mocan N (2005) ldquoCarrots sticks and broken windowsrdquo Journal of Law and

Economics Vol 48 No 1 pp 235-266

Crank J (1990) ldquoThe influence of environmental and organizational factors on police style in

urban and rural environmentsrdquo Journal of Research in Crime and Delinquency Vol 27

pp 166-189

Goodman A (1990) ldquoA model for police officer burnoutrdquo Journal of Business and

Psychology Vol 5 No 1 pp 85-99

Gould E Weinberg B and Mustard D (2002) Crime rates and local labor marketopportunities in the United States 1979ndash1997rdquo Review of Economics and Statistics Vol

84 No 1 pp 45-61

Hipp J and Roussell A (2013) ldquoMicro-and macro-environment population and the

consequences for crime ratesrdquo Social Forces Vol 92 No 2 pp 563-595

Hatry H (1976) ldquoApproaches to productivity measurement and program evaluationrdquo Public

Productivity Review Vol 1 No 3 pp21-28

Hawkins H (2001) ldquoPolice officer burnout a partial replication of Maslachs Burnout

Inventoryrdquo Police Quarterly Vol 4 No 3 pp 343-360

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

983110983145983143983157983154983141 983089983086 983126983119983122983107 983110983151983154983149983157983148983137

983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

1 88 22812 5208 6132 216 348 396 396 264 60 24 72 7

2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 4673 1622 366 147 1613 1051 91 158

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 9830857516 3254 201 278 9830851158 1169 98308595 167

983151983142 C983144983145983148983140983154983141983150 183 702 75 77 983085262 217 983085396 207

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 9830851065 492 98308512 13 983085163 33 98308506 05C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 24 13 02 02 14 01 98308508 05

983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 209 33 20 04 79 19 10 03

983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

983123983145983143983149983137983085983155983153983157983137983154983141983140 1541467 19287 206702 5598

C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

983124983137983138983148983141 4 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142983142983145983139983141983154983155 A983150983150983157983137983148 983126983137983148983157983141 983119983158983141983154 983122983141983152983148983137983139983141983149983141983150983156 C983151983152 (983126983119983122C)

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

983113983150983156983141983154983139983141983152983156 165 36

983123983145983143983149983137983085983155983153983157983137983154983141983140 66

C983144983145983085983155983153983157983137983154983141983140 9846

983152 lt 05

983152lt01

983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 25: PIJPSM-05-2015-0064

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httpslidepdfcomreaderfullpijpsm-05-2015-0064 2530

Herbert S (1998)ldquoPolice subculture reconsideredrdquo Criminology Vol 36 No 2 pp 343-370

Huizinga D and Henry K (2008) ldquoThe effect of arrest and justice system sanctions on

subsequent behavior Findings from longitudinal and other studiesrdquo In The long view of

crime A synthesis of longitudinal research Springer New York pp 220-254

Johnson R (2011) ldquoOfficer attitudes and management influences on police work productivityrdquo

American Journal of Criminal Justice Vol 36 pp 293-306

Kane R (2006) ldquoOn the limits of social control Structural deterrence and the policing of

lsquosuppressiblersquo crimesrdquo Justice Quarterly Vol 23 No 2 pp 186-213

Kubrin C Messner S Deane G McGeever K and Stucky T (2010) ldquoProactive

policing and robbery rates across US citiesrdquo Criminology Vol 48 No 1 pp 57-97

Lersch K (2002) ldquoAre citizen complaints just another measure of officer productivity An

analysis of citizen complaints and officer activity measuresrdquo Police Practice and

Research Vol 3 pp 135-147

Light M and Harris C (2012) Race space and violence exploring spatial dependence in

structural covariates of white and black violent crime in US countiesrdquo Journal of

Quantitative Criminology Vol 28 No 4 pp 559-586

Maxfield M (1982) ldquoService time dispatch time and demand for police services Helping

more by serving lessrdquo Public Administration Review pp 252-263

Maxfield M Lewis D and Szoc R (1980) ldquoProducing official crimes Verified crime reports

as measures of police outputrdquo Social Science Quarterly pp 221-236

Nakosteen R and Zimmer M (2001) ldquoSpouse selection and earnings Evidence of marital

sortingrdquo Economic InquiryVol 39 No 2 pp 201-2013

Shane J (2010) ldquoOrganizational stressors and police performancerdquo Journal of Criminal

Justice Vol 38 No 4 pp 807-818

Shane J (2011) ldquoDaily work experiences and police performancerdquo Police Practice and

Research Vol 13 No 3 pp 1-19

Sherman L Gartin P and Buerger M (1989) ldquoHot spots of predatory crime Routine

activities and the criminology of placerdquoCriminology Vol 27 No 1 pp27-56

Truman J and Rand M (2010) ldquoBureau of Justice Statistics Bulletin National Crime

Victimization Survey Criminal Victimization 2009rdquo US Department of Justice Office of

Justice programs

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2630

Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2730

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983101 983089983088983088lowast + + ) + ) + ) + ) lowast )) minus + + + 983090983088 + ) +983089983088)) minus 983089983088983088 lowast

983086 983097) lowast )

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2830

983124983137983138983148983141 1 E983160983137983149983152983148983141 983151983142 983156983144983141 983116983145983150983139983151983148983150 983120983151983148983145983139983141 D983141983152983137983154983156983149983141983150983156983155 A983150983150983157983137983148 983120983154983151983140983157983139983156983145983158983145983156983161 983122983141983152983151983154983156

983119983142983142983145983139983141983154 983120983154983151983155983141983139983157983156983145983151983150

983122983137983156983141C983110983123

983117983145983150983157983156983141983155983110983125983120

983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

AC983113983122983141983152983151983154983156983155 983123983141983148983141983139983156983145983158983141983155 983127983137983154983150983145983150983143983155 983119983142983142983145983139983145983137983148983155 983127983137983154983154983137983150983156983155 D983125983113983155 983117983145983155983140983141983149983141983137983150983151983154983155 983110983141983148983151983150983145983141983155

1 88 22812 5208 6132 216 348 396 396 264 60 24 72 7

2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

3 72 32496 6312 6600 144 564 444 720 540 84 36 24 12

4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983122983137983150983143983141 983123D 983117983141983137983150

983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 31009830859800 2027 6524

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 5329830851097 1663 8167

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

983110983145983154983155983156983085983116983141 983158983141983148 983126 983137983154983145983137983138983148983141 983155 (983119983142983142983145983139983141983154) 983118=302 983122983137983150983143983141 983123D 983117983141 983137983150

983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

983151983142 C983144983145983148983140983154983141983150 09830855 170 90

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

983110983145983141983148983140 983145983150983142983151983154983149983137983156983145983151983150 983154983141983152983151983154983156983155 0983085227 2153 2530

983124983154983137983142983142983145983139 983139983145983156983137983156983145983151983150983155 249830851246 14632 18642

983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

983110983141983148983151983150983161 983137983154983154983141983155983156983155 098308571 1066 852

983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

983124983137983138983148983141 3 983112983145983141983154983137983154983139983144983145983139983137983148 983116983145983150983141983137983154 983117983151983140983141983148983155 E983155983156983145983149983137983156983145983150983143 983119983142 983142983145983139983141983154983155 A983150983150983157983137983148 983124983154983137983142983142983145983139 C983145983156983137983156983145983151983150983155 983127983137983154983154983137983150983156983155 983117983145983155983140983141983149983141983137983150983151983154983155 983137983150983140 983110983141983148983151983150 983145983141983155

983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

983159983144983145983156983141 13363 32472 9830858921 5664 9830853274 19211 9830854447 3255

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 983085225 99 98308515 03 98308552 24 98308503 03

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 983085168 68 29 14 76 31 22 12

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983117983137983148983141 4673 1622 366 147 1613 1051 91 158

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983124983154983137983142983142983145983139 983155983156983151983152983155 983085983085 983085983085 03 00 09 02 00 00

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983123983141983139983151983150983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142983145983154983155983156) 2603 1778 187 195 809 730 147 160

983124983144983145 983154983140 983155983144983145 983142983156 (983154983141 983142983141 983154983141 983150983139983141 983143983154983151983157983152 983142983145 983154983155983156) 9872 2155 79 213 2532 952 393 132

983113983150983156983141983154983139983141983152983156 32591 5361 758 339 4147 1912 310 484

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C983144983145983085983155983153983157983137983154983141983140 8294 6133 12348 10663

983152 lt 05

983152lt01

983152lt001

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983127A983122983122A983118983124 A983122983122E983123983124983123 983117983113983123DE983117EA983118983119983122 A983122983122E983123983124983123 983110E983116983119983118983129 A983122983122E983123983124983123983124983122A983110983110983113C C983113983124A983124983113983119983118983123

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 3030

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 98308500 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 00 01

983159983144983145983156983141 318 345

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 98308500 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 00 00

983120983154983151983152983141983154983156983161 983139983154983145983149983141983155 983152983141983154 983151983142983142983145983139983141983154 98308502 04

983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 02 05

983110983145983154983155983156983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983119983142983142983145983139983141983154) 983118=302

983117983137983148983141 27 15

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 98308532 31

983151983142 C983144983145983148983140983154983141983150 05 03

983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 00 01

C983137983148 983148983155 983142983151983154 983155983141983154983158983145983139983141 02 01

983124983154983137983142983142983145983139 983155983156983151983152983155 01 00

983110983145 983141983148983140 983145983150983142983151983154983149983137983156983145 983151983150 983154983141 983152983151983154983156983155 02 00

983123983141983139983151983150983140 983155983144983145983142983156 ( 983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 23 12

983124983144983145983154983140 983155983144983145983142983156 (983154983141983142983141983154983141983150983139983141 983143983154983151983157983152 983142 983145983154983155983156) 55 14

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983152 lt 05

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983152lt001

983118983151983156983141 A983148983148 983158983137983154983145983137983138983148983141983155 983137983154983141 983157983150983139983141983150983156983141983154983141983140

Page 26: PIJPSM-05-2015-0064

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Van Meter D (2001) Evaluating dysfunctional police performance A zero-based approach

Charles C Thomas Publisher Springfield IL

Vila B and Kenney D (2002) ldquoTired cops The prevalence and potential consequences of

police fatiguerdquo National Institute of Justice

Vila B Morrison G and Kenney D (2002) ldquoImproving shift schedule and work-hour

policies and practices to increase police officer performance health and safetyrdquo Police

Quarterly Vol 5 No 1 pp 4-24

Vollaard B and Koning P (2009) ldquoThe effect of police on crime disorder and victim

PrecautionEvidence from a Dutch victimization surveyrdquo International Review of Law

and Economics Vol 29 No 4 pp 336-348

Weisburd D Maher L Sherman L Buerger M Cohn E and Petrisino A (1993)

ldquoContrasting crime general and crime specific theory The case of hot spots of crimerdquo

New Directions in Criminological Theory Advances in Criminological Theory Vol 4

pp 45-70

Author Biography

Luke Bonkiewicz is a patrol officer with the Lincoln Police Department

7252019 PIJPSM-05-2015-0064

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983117983145983150983157983156983141983155

983119983142983142983145983139983141983154

A983155983155983145983155983156983117983145983150983157983156983141983155

983113983150983139983145983140983141983150983156983122983141983152983151983154983156983155

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2 95 30072 5424 4116 204 696 228 312 432 84 48 120 8

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4 90 33000 5232 4980 216 192 480 768 240 144 12 72 12

5 91 41724 4824 6048 312 636 132 504 324 108 7 24 24

6 83 23916 7056 6192 144 756 528 996 336 132 36 72 12

7 95 24468 6840 5892 156 624 324 456 480 72 36 120 24

8 90 39972 5196 4920 240 504 384 492 264 36 2 72 24

9 79 25500 4068 5100 336 396 192 684 204 24 36 120 10

10 87 21984 5412 4524 348 552 480 792 312 108 48 84 36

983124983137983138983148983141 2 983123983157983149983149983137983154983161 983123983156983137983156983145983155983156983145983139983155 983142983151983154 983126983137983154983145983137983138983148983141983155

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983120983151983152983157983148983137983156983145983151983150 983140983141 983150983155983145983156983161 20229830856956 1687 4436

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 2628198308576020 16535 49756

983159983144983145983156983141 7398308593 007 083

983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 8009830854800 1203 2521

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983126983145983151983148983141983150983156 983139983154983145983149983141 983152983141983154 983151983142983142983145983139983141983154 194983085372 559 2929

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983111983141983150983140983141983154 (983142983141983149983137983148983141=0 983149983137983148983141=1) 09830851 24 94

983117983137983154983154983145983141983140C983151983144983137983138983145983156983145983150983143 09830851 18 79

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983129983141983137983154983155 983141983160983152983141983154983145983141983150983139983141 198308537 779 1063

C983137983148983148983155 983142983151983154 983155983141983154983158983145983139983141 4819830851011 16121 61365

983124983154983137983142983142983145983139 983155983156983151983152983155 16983085901 14376 20624

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983117983145983155983140983141983149983141983137983150983151983154 983137983154983154983141983155983156983155 19983085403 5965 10663

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983126983119983122C 9830851959830851043 151 24

1983155983156 2983150983140 3983154983140

104 96 102983123983144983145983142983156

7252019 PIJPSM-05-2015-0064

httpslidepdfcomreaderfullpijpsm-05-2015-0064 2930

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983123983141983139983151983150983140983085983116983141983158983141983148 983126983137983154983145983137983138983148983141983155 (983120983137983156983154983151983148 A983154983141983137) 983118=40 983138 983123E 983138 983123E 983138 983123E 983138 983123E

983120983151983152983157983148983137983156983145983151983150 983140983141983150983155983145983156983161 001 003 001 001 98308501 01 00 00

983112983151983157983155983141983144983151983148983140 983149983141983140983145983137983150 983145983150983139983151983149983141 ($) 002 001 983085000 000 00 00 98308500 00

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983126983145983151983148983141983150983156 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 006 004 001 001 98308501 02 01 02

983120983154983151983152983141983154983156983161 983139983154983145983149983141 983154983137983156983141 (983152983141983154 100000) 983085003 005 983085002 001 02 03 98308501 00

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