lable at ScienceDirect

Journal of Air Transport Management 42 (2015) 118e124

Contents lists avai

Journal of Air Transport Management

journal homepage: www.elsevier .com/locate / ja ir t raman

A method for quantifying travel productivity for corporate travelmanagers

Lance SherryCenter for Air Transportation Systems Research (CASTR) at George Mason University (GMU), 4400 University Drive, MS: 4A6, Fairfax, VA 22031, USA

a r t i c l e i n f o

Article history:Received 16 April 2014Received in revised form11 July 2014Accepted 17 September 2014Available online 11 November 2014

Keywords:Business travelCorporate travelCorporate travel managementAirline reliabilityPassenger trip delays

E-mail address: lsherry@gmu.edu.

http://dx.doi.org/10.1016/j.jairtraman.2014.09.0120969-6997/© 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

For large corporations with significant travel budgets, the efficiency in execution of employee travel iscritical to the productivity of the enterprise. Air travel disruptions (i.e. delays, cancellations, missedconnections) prevent employees from performing enterprise related tasks resulting in lost billable rev-enue and unbudgeted Indirect costs (e.g. unplanned overnight stays for stranded passengers, and idletime charges). Since travel disruption data is not readily available to Corporate Travel Managers, theIndirect charges cannot be included in budgets, and the magnitude of lost billable revenue is not known.Further, without measuring the travel delays and their impact, it is not possible to understand the un-derlying causes of the delays to improve the process.

This paper describes a method for providing Corporate Travel Departments travel disruption statisticsand their impact on revenue and profits. The method overcomes the problem of the absence of data byderiving travel delay statistics for corporate travel from publicly available historic airline flight data-bases. The method also uses a travel delay cost model to estimate the financial impact of travel dis-ruptions. The implications of these results on Corporate Travel Management (CTM) productivityimprovement strategies, corporate travel and indirect budgets, contracts with travel providers, and travelinsurance are discussed.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Global production chains, geographically dispersed multi-unitenterprises, and increased inter-firm cooperation have served asthe catalyst for face-to-face meetings resulting in increases inbusiness travel (Gustafson, 2013). As the numbers of employeesthat travel for business, and the value of travel budgets have grown,corporate travel has received increased management attention.Further, efficient travel management has been shown to be wellcorrelatedwith enterprise revenue growth, profit growth, and assetefficiency (Dyment, 2009). As a result large enterprises employCorporate Travel Managers to manage corporate travel enterprise(Holma, 2012; Lubbe, 2003; Mason, 2002).

Corporate Travel Management (CTM) is responsible for theadministration of the enterprises' strategic approach to travel. Thisincludes the travel policy, negotiations with vendors (e.g. corporaterates), day-to-day operation of the corporate travel program, trav-eler safety and security, credit-card management, and Travel andExpense reporting and data management. CTM is particularlycomplex as it involves the coordination and cooperation between

multiple stakeholders with conflicting objectives and processesthat are not directly under their control (Douglas and Lubbe, 2006).For example, the travel brokers making travel reservations cannotbe held accountable for the performance of the travel service pro-viders (i.e. airlines).

Corporate travel department benchmarking studies (e.g.Anderson et al., 1999; Bell and Morey, 1995) assess performance ofthe department on reserving low cost travel (i.e. airfare, hotel, car),labor costs of the travel department (i.e. exempt, salaries, hourly),and travel department general and administrative costs (i.e. fees,technology and space). The benchmarks are generally normalizedby the number of trips booked.

One aspect of the performance of the CTM that is not addressedin these benchmarking studies is the performance of the executionof the travel (i.e. delays). From a corporate financial stand-point,travel delays result in lost billable revenue and in unbudgetedcosts to indirect accounts for unplanned travel expenses such as thecosts for overnight stays for stranded passengers, as well as thetime that cannot be charged to billable projects (i.e. idle time).

Travel delays are not the same as simple flight delays (Bratu andBarnhart, 2005). Travel delays are the result of canceled flights,missed connections, and diverted flights, as well as delayed flights.

L. Sherry / Journal of Air Transport Management 42 (2015) 118e124 119

In the case of canceled flights and missed connections, the traveldisruption is resolved by rebooking the passenger. In some casesthe rebooking results in an unplanned over-night stay. Studies haveshown that one in every four U.S. domestic trips are disrupted, andthat more than 60% of the Total Travel Delays experienced bypassengers are accrued due to canceled flights and missed con-nections (Sherry et al., 2010).

The main reason travel execution is not part of the CTMbenchmarking is due to the lack of availability of travel delay datafor the specific corporate travel itineraries. This paper describes amethod for capturing and reporting travel delays from publiclyavailable historic airline data sources. The method described alsoprovides a model for the effect of air travel delays on lost billablerevenue and (unbudgeted) indirect costs. A case-study for thetravel of a consulting company is provided. The implications of thiscapability to measure travel productivity on CTM are discussed.

The paper is organized as follows: The next section provides anoverview of travel disruptions in air transportation. The followingsection describes a method for measure travel delays and quanti-fying the impact on corporate finances. A case-study for a Wash-ington D.C. consulting company is provided to demonstrate themethod. The implications of these results on CTM processimprovement are discussed.

2. Model of air travel disruptions and costs of air traveldisruptions

Disruptions in corporate air travel that prevent employees fromperforming project related tasks have an impact on billable revenueand indirect charges. This section describes a model for calculatingair travel disruptions from airline flight performance data, and amodel for monetizing the travel disruptions.

2.1. Model of air travel disruptions

A travel disruption is considered to occur when the Travel Delayis in excess of 15 min of the ticketed arrival time (Equation (1)). Theactual arrival time at the destination is the time the passenger ar-rives at the destination airport including delays for rebooking dueto canceled flights and missed connections.

Traveldelay¼Max½ðMinðActualarrivaltime

�TicketedscheduledarrivaltimeÞ;15Þ;0� (1)

Where:

Table 1Summary of trip disruption types for airline travel.

Itinerary type Disruption type Cause

Direct Delayed Flight arrival delay greater than 15 minCanceled Flight is canceled and passenger is

rebooked from origin to destinationConnecting Delayed 2nd leg Flight for 2nd leg is delayed more than

15 minCanceled 1st leg Flight for 1st leg is canceled and

passenger is rebooked from origin todestination

Canceled 2nd leg Flight for 2nd leg is canceled andpassenger is rebooked from hub todestination

Missed connection Flight for 1st leg is delayed beyond theconnection window to the departuretime for the 2nd leg

Actual arrival time ¼ time passenger arrives at destinationincluding delays accrued due to rebooking due to canceledflights or missed connectionsTicketed scheduled arrival time ¼ time passengers are sched-uled to arrive at their destination

Passenger transport via the airline transportation system occurswith one of two types of itineraries, each with distinct disruptioncharacteristics (Table 1). A Direct itinerary has a single flight fromorigin to destination. A Connecting itinerary has two flights. Thefirst flight is from the origin to the hub airport. The second flight isfrom the hub airport to the destination.

Travel disruptions on a Direct itinerary can be the result of adelayed flight or a canceled flight. The travel delay for a delayedDirect itinerary is the difference between the actual flight arrivaltime and the ticketed scheduled flight arrival time. The travel delayof a direct canceled flight is the difference between the passengersrebooked flight arrival time and the original ticketed scheduledflight arrival time. The rebooked flight may be a direct flight or aconnecting flight. In practice, in both cases, a 15 min on-time bufferis added to the scheduled arrival time.

Travel disruptions for a Connecting itinerary are the result ofdelayed flights on the 2nd leg, canceled flights on the 1st or 2nd leg,or delayed flight on the 1st leg resulting in a missed connection forthe 2nd leg. The travel delay for a delayed Connecting itinerary isthe difference between the actual flight arrival time of the flight onthe 2nd leg and the ticketed scheduled flight arrival time of theflight for the 2nd leg.

The travel delay for a canceled Connecting itinerary is the dif-ference between the actual arrival time at the destination on therebooked flight and the ticketed scheduled flight arrival time of the2nd leg flight. If the flight for the 1st leg is canceled, the passengermay be rebooked on a direct flight, through the original connectinghub, or through an alternate connection.

The travel delay of a missed connection Connecting itinerary isthe difference between the actual arrival time at the destination onthe rebooked flight and the ticketed scheduled flight arrival time ofthe 2nd leg flight. In this case, the passenger must be rebooked tothe destination.

Less than 3% of U.S. domestic passengers use itineraries withtwo or more connections. These itineraries would follow rules akinto the connecting itinerary described above.

2.2. A model for monetizing air travel disruptions

Corporate air travel disruptions directly impact the quality timeavailable for interactions with the client, or the time to perform thenecessary tasks on-site. The travel disruptions also impact the timeavailable to the employee to perform other productive tasks notrelated to the travel. In this way travel delays impact billable rev-enue by curtailing the time that can be booked to billable projects.Travel delays also impact indirect accounts. First they are chargedidle time for salaried employs that cannot charge to billable ac-counts. Second, they can be charged over-time when travel delaysextend past the end of the workday. Third, they can be chargedadditional costs for unplanned overnight accommodation forstranded passengers.

The financial impact of corporate air travel disruptions is sum-marized in Fig. 1. The time beyond the ticketed arrival time can bedivided into three segments:

(1) Time for airport processing and local transportation.(2) Time to the end of the workday (at the destination).(3) Time beyond the end of the workday (at the destination)

Fig. 1. Travel delay and its costs are divided into three segments to distinguish revenue lost due to billable hours and indirect costs.

L. Sherry / Journal of Air Transport Management 42 (2015) 118e124120

Time for airport processing and local transportation is consid-ered part of the travel and is billed to the project for which travel istaking place. The time to the end-of-workday is time that would bebilled to the project. When travel delays occur, the portion of thetime that the employee is not able to productively work on a bill-able project is lost billable revenue. This time is also charged to thecorporate indirect account as “idle time.”

The time beyond the end-of-workday would be consideredovertime. When enterprises pay employees for this time and traveldelays occur, the portion of the time that the employee is not ableto productively work on a billable project is lost billable revenue.This time is also charged to the corporate indirect account as “idletime.”

Trip delay costs charged to indirect are the sum of the portion ofnon-productive time during trip delays. This time is divided intotime before the end-of-workday and over-time top account forjurisdictions and jobs that have regulations regarding over-timepay rates (Equation (2)). Lost billable revenue is the sum of theportion of productive time during trip delays (Equation (3)).

Indirect costs ¼X

½ðd_wdðiÞ*ð1� aÞ*hr_wdðiÞ�þX

½ðd_otðiÞ*ð1� aÞ*hr_otðiÞ� þ ½UC� (2)

Lost billable revenue ¼X

½ðd_wdðiÞ*a*b_hrðiÞ�þX

½ðd_otðiÞ*a*b_hrðiÞ� (3)

Where:

d_wd(i)¼ delays before end-of-workday for passenger i (hours)d_ot(i) ¼ delays after end-of-workday for employee i (hours)a ¼ percent of time during delay that is productivehr_wd(i) ¼ hourly rate for workday for employee i ($/hour)hr_ot(i) ¼ hourly rate for over-time for employee i ($/hour)b_hr_wd(i) ¼ billable hourly rate for workday for employee i($/hour)b_hr_ot(i) ¼ billable hourly rate for over-time for employee i($/hour)

3. Method for Corporate Travel Productivity Reporting

To overcome the absence of data for travel delay related costscharged to indirect, and the lost billable revenue, a methodology for

generating a Corporate Travel Productivity Report (CTPR) isdescribed that is based on the use of publicly available data for U.S.domestic flights provided by the Department of Transportation(DOT) Bureau of Transportation Statistics (BTS).

The CTPR is generated through a three step process (Fig. 2).Corporate Employee Travel Itineraries (CETI) are submitted to analgorithm that estimates the Travel Delay statistics. Each flight foreach employee trip is processed to determine the travel delay. Foritineraries that are disrupted due to canceled flights or missedconnections, a rebooking algorithm is used to estimate rebookingdelays. Rebooking delays are a function of the seats available onflights that can be used for rebooking. An estimate of availability ofseats on flights that are candidates for rebooking is generated by analgorithm that estimates the passenger itineraries for these flights.Lastly, the trip delay information is submitted to an algorithm thatmonetizes the delays based on a Corporate Travel Profile (CTP).

3.1. Data sources

The Department of Transportation (DOT) Bureau of Trans-portation Statistics (BTS) provides publicly available data for U.S.domestic flights. Three sets of data are used. The Airline On-TimePerformance data provides flight performance data for individualcommercial flights flown in the U.S. The flight status is providedalong with flight delays for all flights operated by airlines that carryat least one percent of the total passengers. The BTS DB-1B database provides a 10% ticket sample for each quarter for all U.S. do-mestic flights. The BTS T100 data-base provides an aggregate seatcount for all flights operated by airlines that carry at least onepercent of the total passengers. This data is provided as monthlydata.

3.2. Travel delay algorithm

Travel delay for each itinerary is computed by the algorithmsummarized in Fig. 3. Each corporate employee itinerary is pro-cessed with historic flight performance data from the BTS AirlineOn Time Performance data-base. Algorithm uses the rules for traveldelay described in the section on travel disruptions (above). Delaysare computed for direct itineraries, for delayed flights and forcanceled flights. Delays are computed for connecting itineraries fordelayed and canceled flights, and for missed connections.

Fig. 2. The Corporate Travel Productivity Report (CTPR) is generated by a three step process. The travel itineraries are processed by the trip delay algorithm. For passengersdisrupted by canceled flights or missed connections, an algorithm estimates rebooking delays. The trip delays are monetized according to the corporate cost and productivity profile.

Fig. 3. Algorithm for computing air travel delays for flight delays, canceled flights, and missed connections.

L. Sherry / Journal of Air Transport Management 42 (2015) 118e124 121

Overall travel performance statistics are computed based onindividual trip data to describe the overall performance of thetravel execution. Three summary statistics are used: (1) Total TravelDelay, (2) % Itineraries Disrupted, and (3) Average Travel Delay for aDisrupted Itinerary. Total Travel Delay captures the overall magni-tude of the delays. % Itineraries Disrupted provides ameasure of the

degree of disruption. Average Travel Delay provides a measure ofimpact for disrupted corporate travelers.

� Total Travel Delay¼ sum of all individual corporate travel delays� % Itineraries Disrupted ¼ Count of Disrupted Itineraries/TotalCorporate Itineraries

Table 2Example CTPR for hypothetical consultancy based in Tyson Corner, Virginia.

Month: June 2012 Company XX Date prepared:prepared: 7/14/12

(1) Travel summaryRound-trip Itineraries 881One day 162 18%Two-day 189 21%One week 450 51%Two week 80 9%Airports served 36(2) Travel trip delaysTotal passenger travel delay (hours) 944Disrupted itineraries 241 27%One day 37 4%Two-day 39 4%MondayeThursday 144 16%Two week 21 3%Median disrupted travel delay 47 minAverage disrupted travel delay 117 minMaximum disrupted travel delay 17 hUnanticipated overnight stays 19 2.2%(3) CostsTotal costs due to trip disruptions $21,012Indirect costs overtime $10,772 50%Unanticipated expenses (i.e. overnight) $10,240 50%Lost revenue billable projects $74,570

L. Sherry / Journal of Air Transport Management 42 (2015) 118e124122

� Average Delay of Disrupted Itineraries ¼ Total Travel Delay/Count of Disrupted Itineraries

These statistics can also be generated for individual airlines orairports.

3.3. Rebooking seat availability

When a trip is disrupted by a canceled flight or a missedconnection, the passenger must be rebooked. The algorithm createsa candidate list of rebooking options that can serve as an alternatefor the origin and destination. The algorithm assigns passengersaccording to a “day-of-travel” policy in which the passenger isaccommodated to get to destination on the same day. Passengersfrom the canceled flight or missed connection are rebooked basedon the availability of seats on flights by the same airline to arrive onthe same day. If the passenger cannot be accommodated on thesame day, the passenger can be rebooked on another airline. Pas-sengers that cannot be accommodated on the same day are“stranded overnight” and are rebooked on the first available flightthe next day.

The availability of seats on individual flights is projectedthrough a process of estimating the airline passenger itineraries fora given day based on data in the BTS DB-1B data-base, the aircraftseat size for each segment in the BTS T100 data-base, and the flightsscheduled in the BTS AOTP data-base. The rebooking algorithm isdescribed in Fig. 4.

3.4. A case-study Corporate Travel Productivity Report

To demonstrate the concept, a Corporate Travel ProductivityReport (CTPR) for a Washington D.C. based consulting company isgenerated using actual airline flight statistics for June 2012 (Fig. 2).The CPTR, see Table 2, is organized into three sections: (1) Travelsummary, (2) Travel Trip Delays, and (3) Costs.

3.4.1. Travel summaryIn July 2012, this enterprise required 881 round trips from

corporate headquarters. The majority of the air travel required

Fig. 4. Algorithm for rebooking passengers on

MondayeThursday trips (51%). Two day trips accounted for 22% ofthe trips, one day trips 18%. Nine percent (9%) of the travel requiredtwo week trips. The trip duration distribution is shown in Fig. 5.

3.4.2. Travel delaysCorporate travel accrued a total of 944 h of trip delays. Twenty

seven percent (27%) of the corporate travelers experienced a dis-rupted trip. A disproportionate 16% of the 27% disrupted traveloccurred on the MondayeThursday trips. The trip disruption dis-tribution is shown in Fig. 6.

Average trip delay for a disrupted traveler was 117 min. How-ever, 50% of the disrupted travelers experienced a trip delay of lessthan 47. The maximum disruption was 335 min (5.5 h). The

canceled flights and missed connections.

Fig. 5. Distribution of round-trip duration is dominated by MondayeThursday trips(51%) for the hypothetical corporate travel used in the case-study.

Fig. 6. Distribution of Trip delays for hypothetical corporate travel in the case study.

L. Sherry / Journal of Air Transport Management 42 (2015) 118e124 123

distribution of trip delays is shown in Fig. 5. Nineteen trips (2.2%)were disrupted in a way that resulted in an overnight stay.

3.4.3. CostsThe total cost was estimated to be $21K. Charges to indirect

costs amounted to $10.7K. Unanticipated costs amounted to $10.2K.Lost revenue on billable projects was estimated at $74.5K. The total$95K is approximately 5% of the total travel airfare budget of $1.8M.

Fig. 7. Distribution of Round-trips (blue) and Round-trips Disrupted (red) for hypo-thetical corporate travel in the case study. One week round trips (i.e. Mon-dayeThursday) are disrupted at a higher rate than other duration trips. (Forinterpretation of the references to color in this figure legend, the reader is referred tothe web version of this article.)

4. Discussion

As the cost of corporate travel increases, there is increasedpressure to better manage corporate travel and their impact on thefinancial bottom-line. Information on travel disruptions is notavailable to Corporate Travel Managers. This paper has described amethod for calculating travel delays from publicly available flightdata and estimating the impact of these travel delays on lost bill-able revenue and indirect costs. The availability of this informationcan have an impact on CTM by providing an understanding of themagnitude of travel disruptions, their underlying causes, and op-portunities for improvement.

The algorithms for calculation of flight delays are accurate asthey reflect the “physics” of delay propagation in a transportationnetwork as captured in the data used for the analysis. Therebooking algorithm is an estimation based on a 10% sample size in

the BTS DB-1B data-set and monthly aggregate data in the BTS T-100 data set.

4.1. Strategies for improving travel performance

Analysis of the travel disruption data provides several insightsinto the underlying causes and opportunities for improvement.There are several strategies to reduce the number of disrupted trips(27%). The distribution of disrupted trips by trip duration (Fig. 7)shows a disproportionate disruption of 1 week trips (16%) thatrepresent the MondayeThursday “consultant work week”. The oneday, two day and two week trips were disrupted 4%, 4%, 2% of thetime respectively. It may be feasible to stagger travel to avoid thereturn leg late in the afternoon on Thursdays in the mid-Atlanticregion summer convective weather season. During this seasonweather conditions result in pop-up thunderstorms that are diffi-cult for Air Traffic Control to predict resulting in disrupted air travel.

Three airlines accounted for 90% of the total trip delays (Fig. 8).Analysis of the itineraries shows that these airlines operate hub-and-spoke networks with connecting flights which tend to besubject to higher rates of disruption. The well known strategy ofbooking direct flights (instead of connecting flights) does not havemerit in this case. The booked travel is dominated by direct itin-eraries where they are available. Connecting itineraries were usedonly when direct itineraries were not available.

Analysis of the types of disruptions, shows that large portion ofthe total delay time (62%) was the result of rebooking due tomissedconnections and canceled flights. Although only a small percentageof corporate travelers were affected by canceled flights and missedconnections, the magnitude of the delays was large due to therebooking. A strategy that accommodates passengers needingrebooking more efficiently, could reduce the magnitude of thedisruption. In this case study, using the best options for rebooking,including using competing airlines, yields only a 17% reduction inTotal Travel Delays.

Another strategy is to use alternate airlines and/or airports.Three airlines used for corporate travel experienced on-time per-formance lower than 70% (Fig. 9). The best on-time percentage forcorporate trips approached 90%. Analysis of alternate airlines foundthat only 15% of the trips could be booked on a competing airlinewithin ±2 h of the ticketed travel using the same type of itinerary(i.e. direct or connecting). When the restriction on itinerary type is

Fig. 8. Percentage of Passenger Trip Delay (PTD) for hypothetical corporate travel inthe case-study.

Fig. 9. On-time percentage of trips by airline for hypothetical profile of corporate tripstaken in the case-study.

L. Sherry / Journal of Air Transport Management 42 (2015) 118e124124

relaxed, 22% of the trips could have been rebooked on an alternateairline. However, these connecting trips generated no statisticallysignificant advantage (95% confidence interval) in travel delays. Inlarge part, the consolidation of U.S. domestic airlines and the par-titioning of the routes amongst the airlines has reduced alternativeflights. This is especially the case for travel to rural areas and non-hub airports. Further, all flights operating in the same time periodand geographic location, independent of airline, are affected by thesame weather and congestion resulting travel disruptions.

4.2. Improved productivity while traveling

The model of impact on travel delays on the corporate financesincludes a parameter for productivity during the travel delays.Although it may not be possible to eliminate or reduce travel delaysit may be possible to enhance productivity during this period toallow billable work to be conducted (Dresner, 2006; Castillo-Manzano and L�opez-Valpuesta, 2014). There are two componentsto this. First, ubiquitous connectivity to data and tools to performthe work is required (Gratton, 2007). Second, corporate tools anddata must be designed to support this class of remote user takinginto consideration bandwidth limitations as well as security con-siderations. Jurisdiction for enterprise IT is not traditionally a CTMfunction.

Related to productivity improvement is to create the best travelenvironment for productivity. CTM contracts with air travel serviceproviders that allow employees use of airline lounges could assistthose passengers delayed at the airport.

4.3. Improved CTM planning

The CTPR provides the data to improve CTM travel planning. TheCTPR means to accurately track the variable costs of travel dis-ruptions. With this information, indirect budgets can be developedto meet a 90% coverage rate for unexpected charges to corporateindirect accounts and avoid budget overruns. Trends in these costs,particularly increasing costs, can also be monitored and addressedin the budgets in a proactive manner.

One potential application of the CTPR is to incentivize improvedreliability in travel execution via the travel contracts. Although thetravel service provider (i.e. airline) may not have control of all thephenomena that affect travel delays, the contract could providesome assurance of how travel disruptions are dealt with. Forexample, corporate travelers could be given priority in rebookingfor canceled or miss connected flights. These travelers may also beguaranteed “day of travel” rebooking, and guaranteed overnightaccommodation if needed.

As with any uncertain phenomena, there exists the possibility toinsure against losses. The CPTR offers the data to ascertain theutility of “travel disruption” insurance and the value to insure. Theunderlying algorithms of the CTPR provide the mechanism toestablish actuarial rates for determining the value of the traveldisruption insurance relative to the target reliability.

Acknowledgements

David Schaar (Booz Inc.), Kevin Lair, John Shortle and GeorgeDonohue (Center for Air Transportation Systems Research atGeorge Mason University).

References

Anderson, R.I., Lewis, D., Parker, M.E., 1999. Another look at the efficiency ofcorporate travel management departments. J. Trav. Res. 37 (3), 267e272.

Bell, R.A., Morey, R.C., 1995. Increasing the efficiency of Corporate Travel Manage-ment through Macro Benchmarking. J. Trav. Res. 33 (3), 11e20.

Bratu, S., Barnhart, C., 2005. An analysis of passenger delays using flight operationsand passenger booking data. J. Transp. Stat. 13 (1), 1e27.

Castillo-Manzano, J.I., L�opez-Valpuesta, L., August 2014. Living “up in the air”:meeting the frequent flyer passenger. J. Air Transp. Manag. 40, 48e55.

Douglas, A., Lubbe, B.A., 2006. Identifying value conflicts between stakeholders incorporate travel management by applying the soft value management model: asurvey in South Africa. Tour. Manag. 27 (6), 1130e1140.

Dresner, M., 2006. Leisure versus business passengers: similarities, differences, andimplications. J. Air Transp. Manag. 12 (1), 28e32.

Dyment, M., 2009. Business Aviation: an Enterprise Perspective (The S&P from 2003to 2009). NEXA Adviors, LLC, 1250 24th Street, NWSuite 300, Washington, DC20037Washington D.C. www.nexacapital.com.

Gratton, D.A., 2007. WiFi: Enabling True Ubiquitous Connectivity. DevelopingPractical Wireless Applications. Digital Press, pp. 181e215.

Gustafson, P., 2013. Control and commitment in corporate travel management. Res.Transp. Bus. Manag. 9, 21e28.

Holma, A.M., 2012. Interpersonal interaction in business triads: case studies incorporate travel purchasing. J. Purch. Supply Manag. 18 (2), 101e112.

Lubbe, B., 2003. A study of corporate travel management in selected South Africanorganizations and a conceptual model for effective corporate travel manage-ment. South Afr. J. Econ. Manag. Sci. 6 (2), 304e330.

Mason, K.J., 2002. Future trends in business travel decision making. J. Air Transp. 7(1), 47e68.

Sherry, L., Samant, A., Calderom-Meza, G., 2010. Trends in airline passenger tripdelays (2007): a multi-segment itinerary analysis. In: American Institute ofAeronautics and Astronautics: 10th AIAA Aviation Technology, Integration, andOperations (ATIO) Conference. Sept, 2010.