Productivity-Target Difficulty, Performance-Based Pay and ... · conventional task approach and more efficient task approaches that can be identified ... financial incentives tied

Productivity-Target Difficulty, Performance-Based Pay and Outside-the-Box Thinking

Alan Webb

University of Waterloo

Michael G. Williamson

The University of Texas at Austin

Yue (May) Zhang

Northeastern University

April 2011

We thank Jacob Birnberg, Larry Brown, Lynn Hannan, Steven Kachelmeier, Khim Kelly,

Theresa Libby, Tim Mitchell, Andrew Newman, Adam Presslee, Hun-Tong Tan, participants at

the 2011 Management Accounting Section Research Conference, and workshop participants at

Georgia State University, Nanyang Technological University, the University of Texas at Austin,

and University of Waterloo for providing helpful comments. We gratefully acknowledge funding

from a McCombs School of Business Research Excellence Grant and the Social Sciences and

Humanities Research Council of Canada.

Productivity-Target Difficulty, Performance-Based Pay and Outside-the-Box Thinking

ABSTRACT

In an environment where individual productivity can be increased through efforts directed at a

conventional task approach and more efficient task approaches that can be identified through

unconventional thinking, we examine the effects of productivity-target difficulty and pay

contingent on meeting and beating this target. We argue that while challenging targets and

performance-based pay may hinder the discovery of production efficiencies, they can motivate

high productive effort (i.e., motivate individuals to work harder and more productively using

either the conventional task approach or more efficient task approaches when discovered).

Results of a laboratory experiment support our predictions. Individuals assigned both an easy

productivity target and paid a fixed wage identify a greater number of production efficiencies

than those with either challenging targets or performance-based pay. However, individuals with

challenging targets and/or performance-based pay have higher productivity per production

efficiency discovered suggesting these control tools better motivate productive effort.

Collectively, our results suggest that the ultimate effectiveness of these control tools will likely

hinge on the importance of promoting the discovery of production efficiencies relative to

motivating productive effort. In doing so, our results provide a better understanding of

conflicting prescriptions from the practitioner literature and business press.

1

I. INTRODUCTION

In a rapidly changing and highly competitive business environment, many organizations

look to their employees to improve productivity. Employees can boost productivity through

increased efforts using conventional task approaches. They can also direct their efforts toward

identifying and using more efficient ways to perform their tasks. However, identifying

production efficiencies often requires unconventional or “outside-the-box” thinking. Indeed,

many argue that achieving significant productivity breakthroughs is critically dependent on the

extent to which employees move beyond traditional approaches to performing work activities

and, instead, think unconventionally about their tasks to identify efficiencies (Chen and Jones

2005; Magretta 2002).1 We examine the effects of productivity-target difficulty and

performance-based pay in an environment where individual productivity can be increased both

through efforts directed at a conventional task approach and more efficient task approaches that

can be identified through outside-the-box thinking.

Minimal research has examined the influence of management accounting control tools

such as target setting and performance-based pay in such environments. More attention comes

from the practitioner literature and business press in the form of competing prescriptions. Some

advocate the use of challenging productivity targets that can only be achieved by discovering

production efficiencies (e.g., Chen and Jones 2005, Kaplan and Norton 1996; Thompson et al.

1997). Conversely, others advise using easily attainable targets that give individuals the

flexibility (slack) to search for production efficiencies or improved task-related strategies (e.g.,

1 An illustration of unconventional thinking leading to production efficiencies is the advent of manufacturing cells,

which involves „taking the production tools to the product‟, rather than the conventional „taking the product to the

production tools‟ (Chaneski 2005; Sofianopoulou 2006). Such production efficiencies minimized the often costly

and inefficient movement of raw materials and work-in-process. While we provide a manufacturing example and

use the term “production efficiencies,” our research question is relevant to any setting (e.g., non-manufacturing)

where the identification of task improvements is possible through outside-the-box thinking.

2

Wood et al. 1990). Moreover, these articles provide different perspectives as to whether

financial incentives tied to attaining targets further motivate or inhibit productivity (Chen and

Jones 2005; Thompson et al. 1997). Systematic empirical research is needed, both to address the

paucity of academic enquiry in this area, and to help sort out conflicting views that have emerged

in the practitioner literature.

We posit that, relative to easy productivity targets and fixed pay, challenging targets and

performance-based pay have competing effects on two important productivity determinants. On

the one hand, challenging targets and performance-based pay may hurt productivity by hindering

the discovery of production efficiencies. When outside-the-box thinking potentially leads to the

identification of production efficiencies, theory suggests that performance-based pay may overly

focus individuals‟ efforts on the conventional approach to task performance (Amabile 1996).

Additionally, while challenging targets may motivate effort to search for production efficiencies,

cognitive psychology theory suggests that individuals faced with the pressure of attaining tough

targets may not be successful (Beilock et al. 2004; Eysenck 1982; Markman et al. 2006). The

stress and anxiety induced by the assignment of challenging targets is posited to decrease

working memory, which hinders individuals‟ ability to systematically generate and test the

hypotheses necessary to identify more efficient task approaches (Markman et al. 2006).

On the other hand, challenging targets and performance-based pay may enhance

productivity by motivating productive efforts. In environments where all individuals use

straightforward “conventional” task approaches, prior research demonstrates that challenging

productivity targets and performance-based pay induce higher effort and productivity (e.g.,

Chow 1983; Locke and Latham 1990; Sprinkle 2000). To the extent prior research generalizes to

our setting, these control tools may motivate individuals to work harder and more productively

3

using either conventional task approaches or more efficient task approaches when discovered

(i.e., motivate productive effort) relative to those with easy targets and fixed pay.

We examine these potentially competing effects using a multi-period laboratory

experiment where participants receive boxes of letters (18 columns × 7 rows) and, for each,

record the number of times a “search letter” appears. Productivity is defined as the quantity of

correct responses given. Participants can search for the correct answer either by the conventional

way of simply counting the number of times the search letter appears in the box or by identifying

embedded unconventional, but more efficient ways of determining the appropriate counts. These

production efficiencies include patterns within either the box itself or answers across boxes that,

if identified, can significantly increase productivity.

We manipulate two factors between-subjects at two levels each. First, we assign either

(1) an easy productivity target that can be achieved through the conventional way of performing

the task, or (2) a challenging productivity target that can only be achieved by identifying

production efficiencies. Second, participants receive either (1) compensation contingent on

meeting and beating their assigned productivity target, or (2) a fixed wage irrespective of

performance.

We find that participants assigned both an easy productivity target and paid a fixed wage

discovered a greater number of production efficiencies than those with either challenging targets

or performance-based pay. We further demonstrate that those with pay contingent on meeting

and beating easy productivity targets spend less time searching for production efficiencies.

Relative to participants in our easy productivity target/ fixed wage condition, participants

assigned challenging targets report spending just as much time searching for production

efficiencies but found fewer of them. This suggests that the pressure of meeting challenging

4

targets made the time spent searching for production efficiencies less effective. However,

individuals with challenging targets and/or performance-based pay exhibit higher productivity

per production efficiency discovered, suggesting that these control tools motivate greater

productive effort. Ultimately, these competing effects led to similar overall productivity across

conditions in our experiment.

Our results have important implications. First, they suggest that the ultimate effectiveness

of these control tools will hinge on the importance of promoting the discovery of production

efficiencies relative to motivating productive effort. By illustrating the competing effects of

target difficulty and performance-based pay on these two fundamental determinants of

performance, our results provide a better understanding of competing prescriptions from the

practitioner literature and business press. In particular, our results highlight the positive and

negative consequences of commonly used management control tools in settings where

individuals must decide how to allocate their efforts between using conventional approaches to

task performance and searching for and using unconventional, but more efficient, approaches.

Second, by using an experiment to better isolate and understand the effects of control

tools on the tradeoff between conventional efforts and outside-the-box thinking, we also

contribute to field-based research exploring ways to motivate and facilitate the discovery of

production efficiencies. For example, prior research explores the efficacy of employee

suggestion programs, which directly reward individuals or groups for providing innovative ideas

(Welbourne et al. 1995). Research highlights that rewarding ideas can be challenging because the

process involves a high degree of subjectivity, and emphasizing the discovery of ideas rather

than their development and implementation may not necessarily lead to productivity gains (Jain

et al. 2010). Thus, similar to our setting, many firms reward outside-the-box thinking based on

5

whether the innovations can be translated into measurable outcomes (Zingheim and Schuster

2007). By tying rewards to measurable outcomes, prior research suggests that gain-sharing plans

can lead to more efficient production (e.g., less labor hours per unit produced) (Welbourne et al.

1995). However, in the natural environment, it is difficult to isolate whether these gains are

effort-based or caused by more efficient production techniques.2 Our research highlights the

importance of breaking productivity down into these fundamental determinants when

understanding the efficacy of incentive mechanisms such as productivity targets and

performance-based pay.

The remainder of this paper is organized into four sections. The next section provides

background and develops the hypotheses, and section 3 describes the method used to test these

hypotheses. Section 4 presents the results, and section 5 provides a summary discussion of the

results and conclusions.

II. BACKGROUND, THEORY, AND HYPOTHESES

Background and Research Setting

A common key to the success of today‟s organizations has been the ability and

willingness of their managers to engage in unconventional thinking, which involves embracing

“new ways of conceptualizing old problems” (Magretta 2002, p. 90). Importantly,

unconventional or “outside-the-box” thinking is often described as occurring in settings where

well-defined constraints exist with respect to the availability of resources or the amount of time

available to identify solutions (Magretta 2002; Matthews 2004). Thus an on-going challenge in

identifying significant production efficiencies is getting managers to think beyond the existing or

2 Moreover, in the natural environment, it is unclear whether such incentive mechanisms facilitate the discovery of

new production efficiencies or simply motivate individuals to reveal already obvious production efficiencies that

they otherwise have an incentive to withhold (e.g., the information could be used by management to set higher

targets or the efficiencies could lead to a reduction of the labor force) (Sprinkle and Williamson 2004).

6

“conventional” way of doing things, subject to limitations on the resources and time that can be

devoted to doing so. For the purposes of our study, a conventional approach to task performance

is based on prior experience or instruction (i.e., “the way we‟ve always done things”), which,

while sensitive to productive effort, imposes an upper limit on performance potential.

Conversely, production efficiencies, if discovered and successfully implemented, allow for

higher productivity using unconventional approaches to task performance. Importantly, once

discovered, production efficiencies are also sensitive to effort. That is, simply discovering the

efficiencies will not necessarily lead to higher productivity; individuals must still apply effort in

using them.3

To establish an acceptable degree of external validity, we develop our hypotheses in the

context of a setting that our literature review suggests should possess the following features: (1)

individuals can choose the extent to which they will perform a task using a conventional

approach versus attempting to identify production efficiencies; (2) exerting more effort using

conventional techniques will lead to productivity gains; (3) identifying and using production

efficiencies will result in greater productivity gains than the conventional approach; and (4)

constraints exist affecting the extent to which the identification of production efficiencies can

successfully occur (e.g., time limit, task complexity, limited feedback) (Bailey and Bristow

2004; Matthews 2004; Thompson et al. 1997). In all, we create an environment where, subject to

resource constraints, both identifying production efficiencies and working harder using either

conventional or more efficient production approaches (i.e., productive effort) can increase

productivity. Below, we discuss how varying productivity target difficulty and the presence and

3 As an example, the QWERTY keyboards now available on many cellphones can be thought of as a production

efficiency that permits faster and more accurate typing of text messages compared to using alpha numeric keypads.

However, for the productivity gains to be realized, users of phones with QWERTY keyboards still have to exert

effort in using the more efficient technology when typing their messages.

7

absence of pay for meeting and beating an assigned target can combine to influence these two

fundamental elements of productivity.

Productivity Target Difficulty, Performance-Based Pay and Production Efficiencies

Productivity Target Difficulty and the Identification of Production Efficiencies

When determining the level of productivity target difficulty most likely to encourage

discoveries of production efficiencies, both theory and the practitioner literature offer two

potential strategies (Sprinkle et al. 2008). First, set challenging productivity targets that can only

be achieved through the identification of production efficiencies.4 Here, the utility many

individuals derive from target attainment would likely motivate them to expend effort searching

for production efficiencies as the only means of attaining challenging productivity targets

(Hollenbeck and Klein 1987; Locke and Latham, 1990; 2002; Bonner and Sprinkle 2002; Klein

1991; Lee et al. 1997). Second, set productivity targets that can be easily achieved using

conventional approaches such that individuals have the flexibility (slack) to spend time searching

for production efficiencies (Sprinkle et al. 2008). Because this literature suggests that either

challenging or easy targets would be more likely to encourage individuals to spend their scarce

time thinking outside-the-box, we focus our theoretical development on targets of these two

types.5

While both challenging and easy targets could potentially encourage more effortful

outside-the-box thinking, the effectiveness of these efforts may differ across these target types.

Specifically, psychology-based research suggests that the pressure experienced attempting to

4 Importantly, in our setting, a challenging target is similar to traditional definitions of stretch targets in that it can

only be attained by using non-conventional approaches to task performance (Thompson et al. 1997). 5 Moreover, theory suggests that an intermediate productivity target (e.g., one that could be achieved by working

very hard using conventional approaches) would encourage individuals to direct disproportionate efforts to the (less

risky) conventional task approach in order to ensure a high probability of target attainment (e.g., see Sprinkle et al.

2008).

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attain challenging targets can have dysfunctional consequences on the effectiveness of outside-

the-box thinking (Eysenck 1982). In particular, Miller (1960) suggests that at high levels of

arousal (e.g., as induced by challenging targets) the resultant anxiety diverts some of an

individual‟s attention from the task and employs it worrying. More recently, the distraction

hypothesis in cognitive psychology proposes that stress induced by factors such as challenging

targets or performance-based incentives can cause people to “choke under pressure” particularly

on tasks that require information search, evaluation, and strategy formation (Beilock et al, 2004;

Beilock and Carr 2005; Markman et al. 2006, p. 944). Consistent with earlier work on the effects

of excessive arousal (Miller 1960), the distraction hypothesis posits that pressure decreases

working memory, which in turn hinders cognitive performance (Markman et al. 2006).

To the extent challenging targets decrease working memory, the consequences would

likely be particularly negative for time spent attempting to identify production efficiencies. The

unconventional thinking often necessary to identify production efficiencies is inherently complex

without a clearly defined path for successfully performing this activity. As such, the pressure

induced by challenging targets could constrain individuals‟ ability to systematically generate and

test the hypotheses necessary to identify more efficient task approaches.6 If so, the lower

pressure resulting from easy, relative to challenging, targets may actually help facilitate more

effective outside-the-box thinking leading to the discovery of more production efficiencies.7

Performance-Based Pay and the Identification of Production Efficiencies

6 Research in auditing has examined the effects of time pressure on auditors‟ judgments and decisions and generally

documents negative consequences if the pressure is sufficiently high (for a review see DeZoort and Lord 1997). 7 Consistent with this premise, prior experimental research suggests that, when working on a task without clearly

specified paths for successful completion (e.g., predicting stock prices, completing mazes), participants with easy

targets often performed better in these environments than those assigned challenging targets (Huber 1985; Early et

al. 1989).

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Performance-based pay (relative to fixed pay) may also lead to dysfunctional effects with

respect to the identification of production efficiencies (e.g., Humphreys and Revelle 1984;

Woods et al. 1987). In particular, performance-based pay may focus attention on conventional

approaches at the expense of outside-the-box thinking. For example, Shapira (1976) and Pittman

et al. (1982) report that participants receiving performance-based pay focus narrowly on the

attainment of the target in order to receive their reward. As a result, they choose simpler versions

of a game (or a puzzle) that increase their expectancy of success, while those with no

performance-based pay prefer more challenging versions, which they likely find more

intrinsically interesting. Similarly, Amabile (1996) offers that performance-based pay motivates

people to focus excessively on doing what they need to do to earn rewards; as a result they direct

their efforts towards less risky and more predictable task approaches.

The extent to which performance-based pay affects effort directed to the conventional

task approach would likely depend on the difficulty of the assigned productivity target. In our

setting, an easy productivity target is attainable by using the conventional approach to the task.

Thus, individuals who are assigned an easy target and paid to meet or exceed it may

disproportionately use the less risky conventional approach.8 That is, they would spend less time

attempting to identify production efficiencies than if paid a fixed wage.

Since identifying production efficiencies provides the only means of reaching challenging

targets in our setting, providing pay for target attainment would be unlikely to reduce the time

(effort) spent searching for them. However, the effectiveness of linking pay to meeting and

beating challenging targets on outside-the-box thinking may be limited. That is, performance-

8 We employ a budget-linear contract (e.g., Fisher et al. 2003) in our setting to provide individuals an incentive to

exceed their assigned targets. We believe this provides a stronger test of our theory since all participants, even those

with easy targets, can benefit more from identifying production efficiencies than using the conventional approach to

task performance.

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based pay, similar to challenging targets, could induce further pressure (anxiety) on individuals

further hindering the identification of production efficiencies. However, it may also be the case

that challenging targets create a ceiling effect with respect to dysfunctional cognitive

consequences, leaving little room to observe any incremental negative effects of performance-

based pay.

Hypothesis 1

The preceding discussion of the dysfunctional consequences of challenging targets and

performance-based pay in environments requiring information search, evaluation, and strategy

formation (such as that would be required to identify production efficiencies) results in the

following expectations. First, individuals assigned an easy performance target and paid fixed

wages will discover more production efficiencies than those pressured with a challenging target

(regardless of how they are paid).9 Second, the effect of performance-based pay will depend on

productivity target difficulty, such that performance-based pay will lead to fewer discoveries of

production efficiencies when targets are easy. When targets are challenging, performance-based

pay may not have much room to further affect the discovery of production efficiencies. Finally,

there is no clear theoretical basis for predicting whether the dysfunctional effects of combining

an easy target with incentive pay will be more or less severe than those that arise by using

challenging targets. As a result, we make no formal predictions comparing these particular

combinations of target difficulty and pay. Accordingly, our first hypothesis predicts an ordinal

interaction between performance target difficulty and incentive pay. For clarity, we use two

hypotheses to describe the form of the expected interaction:

9 This prediction assumes that individuals will find the task of identifying production efficiencies intrinsically

interesting/ motivating. Thus, individuals will exert effort to discover efficiencies even absent extrinsic rewards for

doing so. This assumption is consistent with prior management accounting research (Bonner and Sprinkle 2002).

11

H1a: Individuals assigned easy targets and fixed wages will discover more production

efficiencies than those assigned challenging targets.

H1b: For individuals assigned easy targets, those paid fixed wages will discover more

production efficiencies than those paid to meet or beat the target.

Productivity Target Difficulty, Performance-Based Pay and Productive Efforts

While challenging targets and performance-based pay may harm productivity by

hindering the discovery of production efficiencies, these control tools may also have a competing

productivity-enhancing effect by motivating productive efforts. For the purpose of our study,

productive effort is distinct from the effort directed towards identifying production efficiencies.

Instead, productive effort refers to the intensity of effort deployed using either the conventional

task approaches or more efficient, unconventional approaches once discovered. As noted earlier,

our predictions assume that even when using unconventional task approaches, greater productive

effort leads to higher productivity.

Our notion of productive effort essentially represents a standardized measure of

productive output, controlling for the approach used to perform a task.10

As such, it permits a

meaningful comparison of the effort inducing effects of targets and incentives across

heterogeneous groups of individuals who differ with respect to their willingness or ability to

identify production efficiencies. Given management‟s general interest in motivating employees

to be as productive as possible, regardless of their ability to identify and employ unconventional

task approaches, we believe productive effort is an important construct to examine (Bonner and

Sprinkle 2002; Locke and Latham 2002; Simons 2000). We base this section‟s hypotheses on

theory and evidence from studies that examine settings where all individuals use similar and

10

Our earlier example of QWERTY versus alpha numeric keyboards on cellphones applies here. Productive effort is

intended to capture the effort exerted by individuals in using either the QWERTY keyboard or the alpha numeric

keyboard. While total productivity (e.g., the number of text messages) will naturally differ across the two task

approaches (keyboard types), productive output captures the effort individuals exert in using their chosen approach.

12

relatively straightforward “conventional” task approaches (e.g., see Chow 1983; Locke and

Latham 1990). Here, where no opportunities exist to identify significant production efficiencies,

more effort generally leads to higher productivity (Bonner and Sprinkle 2002; Locke and Latham

1990).

In settings where only a single straightforward (conventional) approach exists for

performing a task, theory and empirical evidence suggests that both challenging productivity

targets and performance-based pay can lead to higher productivity than easy targets and fixed

wages (e.g., see Chow 1983; Locke and Latham 1990; Sprinkle 2000; Sprinkle and Williamson

2007). First, considerable evidence supports a key prediction of goal theory that there will be a

positive association between target difficulty and effort, which in turn positively impacts

performance (Bonner and Sprinkle 2002; Hollenbeck and Klein 1987; Locke and Latham, 1990;

2002). In fact, prior research demonstrates that individuals continue to work hard even in

situations when it is unlikely that the target will be attained (Bonner and Sprinkle 2002).11

Second, relative to a fixed wage, performance-based pay has also been shown to increase

productivity by enhancing productive effort (Sprinkle 2000).12

We believe that theory related to the productive effort-inducing effects of performance

pay and target difficulty from single-task-approach settings will generalize to a setting where

both conventional and unconventional task approaches can be employed. Prior research suggests

that assigning individuals challenging productivity targets, or providing them with performance-

based pay will lead to higher productive effort regardless of their selected task approach(es).

11

Prior research suggests target difficulty and individual productivity are typically positively related until targets

become excessively difficult, at which point productivity levels off (Locke and Latham, 1990; 2002). 12

While prior research illustrates that challenging targets and performance-based pay can independently boost

productivity in these environments, the joint effects of these control tools are unclear (i.e., it is unclear as to whether

the effects are additive or substitutes) (Bonner and Sprinkle 2002). Thus, we make no predictions about the joint

effects of these control tools.

13

That is, these individuals will not only be more productive when they use conventional task

approaches to solve problems, but they will also be more productive in using unconventional,

more efficient task approaches once identified. Thus, while challenging targets and performance-

based pay may hinder the discovery of production efficiencies, these control tools could still lead

individuals to more productively utilize them once discovered.

In all, the above arguments suggest that, controlling for the increase in productivity

resulting from discoveries of production efficiencies, individuals with either a challenging target

or performance-based pay will have higher productive effort. In other words, challenging targets

and performance-based pay will lead to higher productivity per production efficiency discovered

than easy targets and fixed pay. These predictions, stated in the alternative form, are as follows:

H2a: Individuals with challenging productivity targets will exhibit higher productivity

per production efficiency identified than individuals with easy targets.

H2b: Individuals who are paid to meet or beat a productivity target will exhibit higher

productivity per production efficiency identified than individuals who are paid

fixed wages.

Productivity Target Difficulty, Performance-Based Pay and Productivity

Collectively, challenging targets and performance-based pay may have competing effects

on two important productivity determinants. Our theory development above leads us to expect

that these control tools may hinder the discovery of production efficiencies, but lead to greater

productivity per production efficiency identified. Because theory does not provide a clear basis

for predicting which effect will dominate in affecting overall productivity, we do not develop a

directional prediction. Instead we pose the following research question:

RQ1: Will the difficulty of the assigned productivity target and the use of performance-

based pay affect overall productivity in a setting where conventional and

unconventional approaches can be used to perform a task?

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III. METHOD

Participants

We recruited ninety-eight undergraduate student volunteers from business classes at a

large university. These students participated in one of three 60-minute experimental sessions (27

to 39 participants per session). As participants arrived, they were randomly assigned to a separate

computer terminal, read a set of computerized instructions, and worked individually on a task as

discussed in greater detail below.

Preliminary Period

To familiarize participants with aspects of our task, they worked through a five-minute

preliminary period. From a letter-sized envelope, participants removed a packet with twenty

pages stapled together. Each page contained six boxes with seven rows and eighteen columns of

letters. Each box had a single letter (the search letter) associated with it on the top right hand-side

of the box. Figure 1 contains a screen shot of one page from our task.

Insert Figure 1 about here

The participants‟ task was to count the number of times the search letter appeared in each

box. Participants recorded answers in the appropriate cell in the six columns (numbered box one

through six) by 20 rows (numbered page one through twenty) spreadsheet at their computer. The

program immediately checked the response. If incorrect, a message box appeared informing the

participant of the wrong response, the wrong answer was removed from the spreadsheet, and the

next answer could not be entered into the spreadsheet for five seconds.13

Otherwise, participants

could record an answer for any box at any time (i.e., they did not have to go in order).

13

Participants could record another answer for the box following an incorrect response after the five-second delay.

We locked the spreadsheet following an incorrect response so that it would not be advantageous for participants to

randomly guess answers.

15

Participants received $0.10 for each correct response provided during the preliminary

period. The computer spreadsheet informed participants of the time remaining, the number of

correct answers they had recorded, and the compensation they had earned. The program also

provided a summary of their performance and compensation at the end of the period.

Production Periods

After the preliminary period, participants read additional instructions about the three ten-

minute production periods they would complete next. The task was similar to that of the

preliminary period. However, the instructions now informed participants that there were two

ways to identify answers for each box. First, they could simply count the number of times each

search letter appeared in its corresponding box of letters (the “conventional approach”). Second,

they could identify shortcuts, which in our task represent the “production efficiencies.” As stated

in the instructions, “Shortcuts include patterns in a particular box across the pages, patterns

across boxes within a single page, and/or patterns within a single box which will help identify

the answer.”14

As further described in the instructions, the same shortcuts were used on each new

page of boxes, and they were placed in the same location. So, for example, if participants

identified the shortcut for the first box on the first page of materials, that same shortcut applied to

the first box on each subsequent page. Moreover, the same shortcuts were used in each

production period. So, once discovered, a shortcut could be used repeatedly throughout the

production periods.

We instructed participants that they were free to choose either strategy for determining

correct answers each period. Furthermore, they were informed that, while counting is a reliable

way to complete the task, it takes more time than using the shortcuts once they have been

14

While we did not inform participants until the production periods, these shortcuts were also present during the

preliminary period.

16

discovered. On the other hand, shortcuts will initially take time to discover but will allow the

determination of correct answers much faster. Figure 2 describes each shortcut we used for this

study.15

Insert Figure 2 about here

Before starting the production periods, participants correctly answered several quiz

questions to ensure they understood their instructions and, as discussed below, completed a short

questionnaire. After completing the three ten-minute production periods, participants completed

a short post-experimental questionnaire. Finally, participants received cash compensation for the

preliminary period and, as discussed below, the three production periods. Average compensation

totaled around $18 for the 60-minute session.

Independent and Measured Variables

We manipulated two aspects of participant‟s performance evaluation and reward system

design at two levels, each between subjects. First, we manipulated the difficulty of the

productivity target assigned to them. We assigned half of our participants an easy productivity

target of 10 correct responses per production period. We assigned the other half of our

participants a challenging productivity target of 90 correct responses per production period.16

Second, we manipulate participants‟ incentive contract. Half of our participants received

a fixed-wage contract that paid them $7 per production period irrespective of their performance.

The other half of our participants received a “bang-linear” performance-based contract (Fisher et

al. 2003). Specifically, these participants received a fixed wage of $2, a bonus of $0.10 × the

15

We conducted several pilot tests to develop shortcuts that were detectable but not so obvious that the task would

be easy to perform. All six shortcuts were discovered at least once and, as will be reported in the next section, on

average participants across all conditions found about 50% of the available shortcuts. 16

Consistent with definitions in the literature, we consider an easy target as one achievable almost 100 percent of

the time and a challenging productivity target as one achievable between 25 and 40 percent of the time (e.g., see

Locke and Latham 1990; Merchant and Van der Stede 2007). We chose 10 (90) to be our easy (challenging)

productivity target because pilot results suggested that this productivity target is achieved by 100 percent (25 to 40

percent) of our participants.

17

assigned productivity target as a bonus for reaching this target, and a piece rate of $0.10 for

every correct response for exceeding their assigned productivity target. In essence, participants

received a $0.10 piece-rate if their performance exceeded their assigned productivity target.17

Dependent Variables

To determine the number of shortcuts discovered by participants, we asked them to

describe the shortcuts found and the period in which they were discovered. To validate the self-

reports we had an independent coder, blind to the study‟s hypotheses, review the pattern of

responses electronically collected for each participant to determine if it corresponded with the

self-reported shortcuts discovered. For example, a participant who indicated she had discovered

the shortcut for box 1, and consecutively entered the correct response for that box several times

before providing a response for another box (on any page) was deemed by the coder to have

discovered that shortcut. Where the pattern of responses did not clearly indicate whether a self-

reported shortcut had been discovered, the coder only gave credit where the description provided

by the participant unambiguously corresponded to the actual shortcuts embedded in the

instrument. This approach resulted in a high correlation between the coded and self-reported

number of shortcuts (r = 0.94, p < 0.001) and the coded number of shortcuts discovered is highly

correlated with the total number of correct responses for the three production periods (r = 0.77, p

< 0.001). As a result, we believe the construct validity of our shortcuts discovered measure is

acceptable. We used the number of correct responses each period as our measure of overall

productivity and divide that amount by the total number of shortcuts discovered to determine

productivity per production efficiency. As discussed below, by controlling for productivity

17

To ensure equivalent compensation magnitudes across our fixed wage and performance-based contract conditions,

we ran a pilot study and set our pay parameters such that $7 = $2 + ($0.10 × average pilot performance per

production period).

18

caused by discoveries of shortcuts, this measure captures productivity resulting from productive

efforts.

IV. RESULTS

Test of Hypothesis 1

Our first hypothesis predicts an ordinal interaction such that participants in the fixed

wage, easy productivity target condition will identify more production efficiencies than those in

the challenging conditions. In addition, participants in the fixed wage, easy target condition will

identify a greater number of production efficiencies than those paid to meet or beat an easy

target. Panel A of Table 1 provides descriptive statistics for the number of times each shortcut

(production efficiency) was discovered and shows that all shortcuts were discovered at least once

with shortcuts 1, 2 and 6 discovered more frequently than the others.18

Panel B shows the

average number of Shortcuts discovered across the three production periods, by experimental

condition.

Panel C of Table 1 provides the results of an ANCOVA with the total number of

Shortcuts as the dependent variable, with Productivity Target difficulty and Contract type as our

independent variables, and Gender as the covariate.19

As reported in Panel C, we observe a

significant main effect for Contract (F = 5.17, p = 0.01) qualified by a significant Contract ×

Productivity Target (F = 5.91, p = 0.01) interaction.20

In Panel D, we report the results of the

contrast tests used to evaluate Hypotheses 1a and 1b. As indicated by the descriptive statistics in

Panel B, and the results reported in Panel D of Table 1, participants in the fixed wage/easy target

condition identified significantly more production efficiencies than participants in the

18

The timing of shortcut discovery is as follows: 30% period 1, 51% period 2, and 19% period 3. 19

Prior research suggests that the success solving puzzles such as those embedded within our experimental task

differs across gender (Amabile 1996). Thus, we use a gender indicator (male = 0, female = 1) as a covariate to

control for this possibility and include it in the reported results. 20

Reported results are based on one-tailed tests unless otherwise noted.

19

challenging goal conditions (t = 2.069, p = 0.02). On average, participants with an easy target

and a fixed wage discovered about 3.8 shortcuts compared to 3.0 in the two challenging target

conditions. The contrast results in Panel D also show that participants assigned an easy target and

fixed wage discovered significantly more shortcuts than their counterparts with an easy target

and performance-based pay who on average found only 2.4 shortcuts (t = 3.147, p = 0.002).

Moreover, for participants assigned a challenging target, those paid under a performance-based

contract discovered the same number of shortcuts as those paid under a fixed wage contract.

Thus it appears that challenging targets, regardless of the type of incentive contract used, created

dysfunctional consequences with respect to participants‟ ability to identify shortcuts. Overall,

these results support H1a and H1b.21

Insert Table 1 about here

To evaluate whether participants‟ behavior is consistent with the reasoning underlying

our first hypothesis, we first examine the amount of time spent looking for shortcuts in each

condition. We asked participants to self-report the percentage of time spent each period

searching for shortcuts. We convert this to “time” by multiplying their self-reported percentages

by the 10 minutes available each production period. Time spent searching for shortcuts is

significantly correlated with the number of shortcuts actually found (r = 0.36, p < 0.001), which

we believe supports the construct validity of the self-reported measure of time allocation.

Table 2, Panel A reports descriptive statistics for the average amount of Time searching

for shortcuts for the three production periods for each condition, and Panel B reports the results

of an ANCOVA (same factors as above) for this measure. We observe a significant Productivity

Target main effect (F = 2.81, p = 0.05) qualified by a significant Productivity Target × Contract

21

Results (not tabulated) also show that, consistent with our predictions, participants with an easy target and fixed

wage discovered more shortcuts than the other three conditions combined (t = 2.74, p < 0.01).

20

interaction (F = 2.73, p = 0.05). The effects of target difficulty on searching Time are significant

for participants working under a performance-based contract (not tabulated, F = 6.48, p < 0.05)

but not a fixed-wage contract (not-tabulated, F = 0.01, p > 0.90). As expected, participants with

an easy target and a fixed wage contract spent significantly more time (5 minutes) searching for

shortcuts than those with an easy target and a performance-based contract (3.9 minutes) (not

tabulated, F = 2.47, p < 0.10, one-tailed). For those with challenging targets, the Time spent

searching for shortcuts did not differ across contracts (not tabulated, F = 0.61, p > 0.40).


We also expected that the pressure associated with meeting a challenging target would

make the time spent searching for shortcuts less effective. We examine this possibility by

dividing the Time participants spent searching for shortcuts by the number of shortcuts they

discovered (i.e., we examine Time per Shortcut discovered).22

Descriptive statistics for Time per

Shortcut are reported in Table 3, Panel A, with ANCOVA (same factors as above) results in

Panel B.

Consistent with our theory development, we observe a significant main effect of

Productivity Target (F = 2.94, p = 0.04), indicating that participants assigned challenging targets

were less efficient finding shortcuts than those assigned an easy target. As shown in Panel A of

Table 3, participants with an easy target spent an average of 4.72 minutes per shortcut discovered

compared to 5.91 minutes per shortcut for participants with a challenging target.23

We also

observe a marginally significant main effect (F = 2.13, p = 0.07) of Contract type with the means

in Panel A showing that performance-based pay leads participants to be less efficient finding

22

To simplify the reporting for this measure, we divide the total number of shortcuts discovered by the total time

spent looking for shortcuts across all three production periods. 23

We also observe that participants assigned challenging targets make marginally significantly more mistakes than

those in the easy target condition, which is suggestive of higher levels of stress or anxiety (F = 1.74, one-tailed p =

0.09).

21

production efficiencies than those paid a fixed wage. As reported in Panel A of Table 3,

participants paid a fixed wage spent about 4.71 minutes finding each shortcut while those under

the performance-based contract spent 5.92 minutes per shortcut discovered. Finally, results of

analysis (not tabulated) indicate that Time per Shortcut in the fixed wage/ easy target condition is

significantly lower than the other three conditions combined (t = 1.54, p < 0.10). Overall, these

results indicate that the pressure induced both by challenging productivity targets and

performance-based pay appear to result in less efficient use of the time spent trying to discover

shortcuts.


Test of Hypotheses 2a, 2b, and Research Question 1

Our second set of hypotheses predict that either a challenging target (H2a) or

performance-based pay (H2b) will lead to higher productivity per production efficiency

identified relative to an easy target or fixed pay. Panel A of Table 4 reports the descriptive

statistics by condition for Productivity per Shortcut in period three (Period three productivity

total shortcuts found) and Panel B summarizes the results of an ANCOVA (same factors as

above) used to evaluate the results.24

During period three (i.e., the final production period),

participants would have been utilizing all discovered shortcuts making productivity in this period

the most appropriate dependent measure for our analysis.

Consistent with our expectations, Productivity Target has a significant effect on

Productivity per Shortcut (F = 2.72, p = 0.05), with participants assigned a challenging target

being more productive than those assigned an easy target (respectively, means 23.5 and 21.7).

There is also a significant Contract type effect (F = 6.51, p < 0.01), with participants in the

24

Table 4 includes only those results for the 87 participants who discovered at least one production efficiency.

Including the productivity scores of the 11 participants who did not discover a shortcut yields similar statistical

inferences.

22

performance-based pay conditions (mean = 24.0) exhibiting greater Productivity per Shortcut

than those in the fixed wage conditions (mean = 21.3). Finally, results of analysis (not tabulated)

indicate that Productivity per Shortcut in the fixed wage/easy target condition is significantly

lower than the other three conditions combined (t = 3.26, p < 0.01).25


Given the competing effects of target difficulty and performance-based pay predicted by

our first two hypotheses, our research question examines the effects of these control tools on

total productivity. Table 5, Panel A presents descriptive statistics for Productivity for period

three since, by the beginning of the final period, over 80% of the total number of shortcuts that

would eventually be discovered had been found. Thus the competing effects of targets and

performance pay should be observable by period three. Table 5, Panel B summarizes the results

of an ANCOVA (same factors as above) used to evaluate the research question.26

Only the

Contract × Productivity Target interaction is marginally significant (F = 3.66, p = 0.06, two-

tailed) in Panel B.

The descriptive results in Panel A show that the interaction is driven by the decrease in

productivity for participants assigned an easy target that arises under the performance-based

contract compared to fixed wage (respectively, means = 55.8 and 75.1). Results (not tabulated)

25

As a second measure of productive effort, we also use OLS regression to estimate the effect on productivity of our

experimental conditions controlling for the number of shortcuts found. Here, we estimate the following equation

Productivityperiod 3 = a + b1(Total Short Cuts Discovered) + b2(Challenging Target Dummy Variable) +

b3(Performance-Based Pay Dummy Variable) + b4(Challenging Target x Performance-Based Pay) + b5(Gender

Dummy Variable) + b6(Preliminary Period Productivity) + b7(Years in College) + . Further supporting H2a and

H2b, regression results suggest that, controlling for the total number of discovered shortcuts (b1= 16.08, t = 17.10, p

< 0.01), those with challenging targets (b2= 8.00, t = 2.24, p = 0.01) and performance-based pay (b3= 5.11, t = 1.37,

p = 0.09) exhibited higher levels of productivity. The person-specific controls (b5 through b7) are all significant (all

p‟s < 0.10). 26

Results from a repeated measures ANCOVA (not tabulated) show that none of the two-way or three-way

interactions involving Period and either Productivity Target or Contract are significant (all p-values > 0.15).

Productivity means across period 1, 2, and 3 by experimental condition are as follows: 31.21, 54.87, and 75.08 in

easy/ fixed; 25.80, 55.52, and 70.20 in challenging/ fixed; 24.80, 40.68, and 55.76 easy/ performance-based; 27.46,

48.42, and 71.92 challenging/ performance-based.

23

show that this decrease is significant (F = 5.76, p < 0.05, two-tailed). Thus the negative effect of

easy targets and performance-based pay on the discovery of shortcuts (Table 1, Hypothesis 1b)

was not offset by the positive effect of this combination on productive effort found in support of

Hypothesis 2b (Table 4). Conversely, analysis (not tabulated) also shows that productivity does

not differ significantly (F = 0.20, p > 0.80) among participants assigned an easy target and paid a

fixed wage and those assigned challenging targets (fixed and performance-based pay).

Importantly, this comparison indicates that the beneficial effect of challenging targets on

productive effort (H2a) offsets their negative impact on the discovery of production efficiencies

(H1a).


V. CONCLUSIONS

In an environment where individual productivity can be increased through efforts

directed at either a conventional task approach or more efficient task approaches that can be

identified through outside-the-box thinking, we use an experiment to examine the effects of

productivity-target difficulty and pay contingent on meeting and beating the productivity target.

Our results suggest that challenging targets and performance-based pay have competing effects

on two important productivity determinants. On the one hand, both challenging productivity

targets and performance-based pay hurt productivity by hindering the discovery of production

efficiencies. Participants assigned an easy target and paid a fixed wage identified the most

production efficiencies. On the other hand, challenging targets and performance-based pay both

enhanced productive effort (i.e., motivated participants to be more productive per production

efficiency identified). Our results suggest that the ultimate effectiveness of these control tools

will hinge on the importance of promoting the discovery of production efficiencies relative to

24

motivating productive effort. By illustrating the competing effects of target difficulty and

performance-based pay on these two fundamental determinants of performance, our results

provide a better understanding of conflicting prescriptions from the practitioner literature and the

business press.

Our results also have interesting implications for the burgeoning management accounting

literature examining the impact of reward system design on risk-taking and creativity. First, we

contribute to prior accounting experimental research examining how productivity target setting

affects risk-taking (i.e., Sprinkle et al. 2008). Prior research typically operationalizes risk-taking

as a choice between distributions with varying means and variances. While prior research

suggests that challenging targets can promote effective risk-taking, our results suggest that this

finding may not generalize to an environment where risk-taking requires cognitive effort. That is,

while challenging targets encouraged our participants to take risks by spending time thinking

unconventionally about their task, our results suggest that the pressure of meeting these targets

led to ineffective use of this time.

Second, while prior research suggests that performance-based pay does not impair

performance on creative tasks (Kachelmeier et al. 2008; Kachelmeier and Williamson 2010), our

results suggest that it can hinder the unconventional thinking often required to identify

production efficiencies. Unlike this prior research, our task had a conventional approach (i.e.,

prior research employed a creative open-ended task), and performance-based pay coupled with

easy targets encouraged participants to fixate on this conventional approach. However, additional

research is needed to contribute to a better understanding of when performance-based pay

promotes or impairs performance on creative and/or outside-the-box thinking.

25

Moreover, limitations of our study provide additional opportunities for future research.

First, we examine only two goal levels, easy and challenging. We do so because the literature

suggests that either easy or challenging targets would most likely encourage individuals to spend

time searching for production efficiencies. That said, future research may examine whether and

when more finely grained levels of goal difficulty better promote productivity in similar settings.

Second, not all of our participants may have perceived performance-based pay as directly

rewarding them for discovering production efficiencies. Instead, some may have interpreted the

assigned targets as the productivity level they could attain simply by counting letters. This may

have led some participants who were assigned the challenging target to underestimate the

importance of looking for shortcuts. Thus, the effects of more closely linking compensation to

discovering production efficiencies would be useful to explore in future research. Finally,

although we used three 10-minute production periods in our experiment, it may be that the

benefits of challenging (stretch) targets on the discovery of production efficiencies may take

longer to emerge because of the initial dysfunctional effects related to pressure, stress and so on.

Future research could examine the consequences of these targets over a longer period of time.

26

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29

FIGURE 1

Task Example

1 . E

A C M K Y S A Z I Q X G R B E J A S J P T M W L L A V U T L G R K H H B B I D G Q N D M O K O Z B L P Z A F V L Q R P O V I W L D X Y B N Q D Z J J Z Z F H D J Y V M B N H A Q B K Z N Z J P I A H V T D X Z B L C S X Y K R D G V A A K Y D V Y N O W D T

2 . L

O X K U L N L T E I G F N Y P O L T T H L R B C E V C L S L L Q T L L I L Y F P O E L I L F N U V W Q V L I Q L Q X Z L J F J L L L M L L L E L L L R G B Q X E B F R G L N J L Z P Z U L L S S I Y L L Y L L Z A L T L L L W C L K R L S A A L D T L Z B B

3 . Y

B Y Y S P I R Y A K Y M C S R O T Y Y O H R W S B U Y D D T Y Y L T Y M H Y R Z Z Y K F B J D Q Y F Y Y J H Y Y C Y O S Y Y R Y Z Y Z C U Y Y Y Y T T Y V O Y V A Y Q Y F M J Y C G Y Y T H R V Y Y E Z Y J K Y U Y I Y F V J R P G T V Y V K G R L C Y S E

4 . Y

X H J B W H J W O A I E B H G G G G Z B L K D L Y Y Y O R C A T J P G B W A F U G P V U Z D G R T S L C H N V K D K D Y H H F F R S A H C K D M G Y B J E Y D L K X K W L M L C X A S Y W N X D I G Y Y Y N H G P Y R S H E F U L L V O V M Y L Y Y W Y R O

5 . F

Y T M A S Q C Z J O W R F H G Y G P I F D Y M M Y L Y F E E W F F T U A Q U J G S D A K G B D I E P F L A Z R A J B F F A A F F D F P C B X Y S D O S M L F F Y F U R I B L Q R V F W O I A F Q I L H T G Q G E X M G B I Y E R Z K V J P M V X I A Y Q A Z

6 . R

S H B H B B Y H D Z Q E B L L Z U F T Q A O X O V F C A Q C H A K V Q L L W P G O Q N O B U V G S I M Y U G J L C H H U T O K K Z S X F B A J X J J L G J J Z E U A E J R V S A V W E K O I P O V K N Q S Z R G J N T X Z T E K O O A C Z T O I C R T I M J

30

FIGURE 2

Task Shortcuts

Box one Across pages, the answers repeated 1, 2, and 3. That is, the answer to Box one, Page one was 1;

Box one, Page two was 2; Box one, Page three was 3; Box one, Page 4 was 1; etc.

Box two Across pages, the answers counted down by two. Specifically, the answer to Box two, Page one

was 40; Box two, Page two was 38; Box two, Page three was 36; etc.

Box three

On each page, the answer was the sum of the answers to Box one and Box two. For example, on

page 1, the answer to Box one was 1 and the answer to Box two was 40. Thus, the answer to Box

three was 41.

Box four

Within the first row of the box, the column in which a repeating letter first appears. Please see

the example below.

N

X W M D L L L L L L L L L L L L L L

U F R Z S H Z Y W S G K U A T C X B

D X U F D L L O Q H X M R J Z S X O

H T N P A C U L U B P P J N C M V G

N V A W F Q M C X X E N F Q U Y R U

P B U H H D Z W K L H R N P S Y Z Q

D H B Z K P W P V S U J Z R X V P L

Answer: 5

Box five

On each page, the answer was the answer to Box four plus one. For example, if the answer to

Page one, Box four was 5, then the answer to Page one, Box five was 6.

Box six Across pages, the answers counted up by one. Specifically, the answer to Box six, Page one was

3; Box two, Page two was 4; Box two, Page three was 5; etc.

Column 5, the column where the

first repeating letter, L, appears

31

TABLE 1

The Effect of Productivity Target and Contract on Number of Shortcuts Discovered

Panel A: Number (percentage) of Participants Discovering Each Shortcut

Participants who

Discovered

Shortcut Number %

1 85 86.7

2 75 76.5

3 52 53.1

4 1 1.0

5 25 25.5

6 60 61.2

Panel B: Means (Standard Deviations) for Shortcuts Discovereda (n = 98)

Easy Target Challenging Target Average

Fixed Wage Contract

3.75

(1.42)

n = 24

3.04

(1.48)

n = 25

3.39

(1.48)

Performance-Based

Contract

2.36

(1.65)

n = 25

3.04

(1.20)

n = 24

2.69

(1.48)

Average 3.04

(1.68)

3.04

(1.34)

Panel C: Analysis of Variance

Factor Df

Sum of

Squares F

p-valuee

CONTRACTb 1 10.89 5.17 .01

PRODUCTIVITY TARGETc 1 0.02 0.01 .93 CONTRACT × PRODUCTIVITY TARGET 1 12.45 5.91 .01 GENDERd 1 2.30 1.09 .30

Error 93

Panel D: Planned Contrasts

t-statistic p-value

H1a Fixed Wage/Easy Target vs. Challenging Target conditions 2.069 0.02

H1b Fixed Wage/Easy Target vs. Performance Based Contract/Easy Target 3.147 0.002 aTotal number of shortcuts discovered across the three production periods.

bContract: 0 = fixed wage; 1 = performance-based.

cProductivity Target: 0 = easy target (10); 1 = challenging target (90).

dGender: 0 = male; 1 = female.

eReported p-values are two-tailed unless testing a one-tailed prediction, as signified by bold face.

32

TABLE 2

Effects of Contract and Productivity Target on Time Spent Looking for Shortcuts per

Period

Panel A: Means (Standard Deviations) for Minutes Spent Looking for Shortcutsa (n = 98)


Fixed Wage Contract

4.99 (2.54)

n=24

4.90 (2.81)

n=25

4.95 (2.65)

Performance-Based

Contract 3.90

(2.47)

n=25

5.61 (2.33)

n=24

4.73 (2.53)

Average 4.43 (2.53)

5.25 (2.59)

Panel B: Analysis of Variance

Factor df Sum of Squares F

p-value

b CONTRACT 1 1.76 0.28 .60

PRODUCTIVITY TARGET 1 17.73 2.81 .10

CONTRACT × PRODUCTIVITY TARGET 1 17.22 2.73 .05

GENDER 1 23.09 3.66 .06

Error 93

aAverage time spent searching for shortcuts per period for the three production periods based on participants self-

reported time allocation. bReported p-values are two-tailed unless testing a one-tailed prediction, as signified by bold face.

33

TABLE 3

Effects of Contract and Productivity Target on Time Spent per Shortcut Found

Panel A: Means (Standard Deviations) for Minutes Spent per Shortcut Founda (n = 98)


Fixed Wage Contract

4.31 (2.69)

n=24

5.10 (3.19)

n=25

4.71 (2.95)

Performance-Based

Contract 5.13

(2.50)

n=25

6.71 (5.48)

n=24

5.92 (4.29)

Average 4.72 (2.60)

5.91 (4.51)



p-value

b CONTRACT 1 27.41 2.13 .07



GENDER 1 68.52 5.34 .02

Error 93

aTotal time spent searching for shortcuts across the three production periods divided by the total number of shortcuts

discovered. bReported p-values are two-tailed unless testing a one-tailed prediction, as signified by bold face.

34

TABLE 4

Effects of Contract and Productivity Target on Productivity per Shortcut Discovered

Panel A: Means (Standard Deviations) for Productivity per Shortcut Discovered Period Threea

(n = 87)


Fixed Wage Contract

19.79 (4.05)

n=22

22.80 (3.49)

n=22

21.29 (4.03)

Performance-Based

Contract 23.86 (6.03)

n=20

24.12 (5.01)

n=23

24.00 (5.45)

Average 21.73 (5.43)

23.48 (4.34)



p-value

a CONTRACT 1 145.71 6.51 .007



GENDER 1 9.45 0.42 .52

Error 82

aProductivity in period three divided by total number of shortcuts discovered for all three production periods.

bReported p-values are two-tailed unless testing a one-tailed prediction, as signified by bold face.

35

TABLE 5

The Effect of Productivity Target and Contract on Period Three Productivity

Panel A: Means (Standard Deviations) for Period Three Productivitya


Fixed Wage Contract

75.08 (27.90) n = 24

70.20 (29.21) n = 25

72.59 (28.38)

Performance-Based

Contract 55.76

(27.82) n = 25

71.92 (24.45) n = 24

63.67 (27.20)

Average 65.22 (29.24)

71.04 (26.72)



p-value

b CONTRACT 1 1802.68 2.38 .13



GENDER 1 139.62 0.18 .67

Error 93

aTotal productivity for the third production period.

bReported p-values are two-tailed.

Documents

Productivity-Target Difficulty, Performance-Based Pay and ... · conventional task approach and more efficient task approaches that can be identified ... financial incentives tied