IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v68y2022i9p6697-6715.html
   My bibliography  Save this article

Impact of Motivation and Workload on Service Time Components: An Empirical Analysis of Call Center Operations

Author

Listed:
  • Ahmad M. Ashkanani

    (College of Business Administration, Kuwait University, Kuwait)

  • Benjamin B. Dunford

    (Krannert School of Management, Purdue University, West Lafayette, Indiana 47906)

  • Kevin J. Mumford

    (Krannert School of Management, Purdue University, West Lafayette, Indiana 47906)

Abstract

We study the joint effects of motivation and workload on human servers’ service time. Using operational and survey data from a call center with a pooled queue structure and limited financial incentives, we examine how individual differences between servers’ trait intrinsic motivation (IM) and extrinsic motivation (EM) impact their average offline, online, and total service times in response to changing workloads. We find significant differences in the patterns of workload and service time relationships across different stages of the service request between servers possessing different combinations of trait motivation. For example, servers with a combination of high IM and low EM were approximately 15% (161%) faster in processing the offline portion of service requests than their peers with the opposite combination (low and high) when workload levels were low (high), respectively. In contrast, servers with high IM-low EM were approximately 35% (5%) slower in processing the online portion of service requests than their low IM-high EM counterparts when workload levels were low (high), respectively. Our findings suggest important nuances in how servers with different trait motivation types respond to changing workload across different stages of the service request. The behavioral pattern shown by high IM-low EM servers is consistent with the preferences of productivity-seeking call center managers who favor speedup and slowdown at certain stages of the service request, conditional to workload. These findings underscore the importance of accounting for trait-based individual differences for a more complete understanding of the complex relationship between workload and service time.

Suggested Citation

  • Ahmad M. Ashkanani & Benjamin B. Dunford & Kevin J. Mumford, 2022. "Impact of Motivation and Workload on Service Time Components: An Empirical Analysis of Call Center Operations," Management Science, INFORMS, vol. 68(9), pages 6697-6715, September.
    • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:9:p:6697-6715
    DOI: 10.1287/mnsc.2022.4491
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2022.4491
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2022.4491?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tom Fangyun Tan & Serguei Netessine, 2014. "When Does the Devil Make Work? An Empirical Study of the Impact of Workload on Worker Productivity," Management Science, INFORMS, vol. 60(6), pages 1574-1593, June.
    2. Robert J. Batt & Christian Terwiesch, 2017. "Early Task Initiation and Other Load-Adaptive Mechanisms in the Emergency Department," Management Science, INFORMS, vol. 63(11), pages 3531-3551, November.
    3. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    4. Delasay, Mohammad & Ingolfsson, Armann & Kolfal, Bora & Schultz, Kenneth, 2019. "Load effect on service times," European Journal of Operational Research, Elsevier, vol. 279(3), pages 673-686.
    5. Noah Gans & Ger Koole & Avishai Mandelbaum, 2003. "Telephone Call Centers: Tutorial, Review, and Research Prospects," Manufacturing & Service Operations Management, INFORMS, vol. 5(2), pages 79-141, September.
    6. Jillian A. Berry Jaeker & Anita L. Tucker, 2017. "Past the Point of Speeding Up: The Negative Effects of Workload Saturation on Efficiency and Patient Severity," Management Science, INFORMS, vol. 63(4), pages 1042-1062, April.
    7. Diwas S. Kc & Christian Terwiesch, 2009. "Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations," Management Science, INFORMS, vol. 55(9), pages 1486-1498, September.
    8. Stephen Deery & Roderick Iverson & Janet Walsh, 2002. "Work Relationships in Telephone Call Centres: Understanding Emotional Exhaustion and Employee Withdrawal," Journal of Management Studies, Wiley Blackwell, vol. 39(4), pages 471-496, June.
    9. Hummy Song & Anita L. Tucker & Karen L. Murrell, 2015. "The Diseconomies of Queue Pooling: An Empirical Investigation of Emergency Department Length of Stay," Management Science, INFORMS, vol. 61(12), pages 3032-3053, December.
    10. Valery Yakubovich & Daniela Lup, 2006. "Stages of the Recruitment Process and the Referrer’s Performance Effect," Organization Science, INFORMS, vol. 17(6), pages 710-723, December.
    11. Masha Shunko & Julie Niederhoff & Yaroslav Rosokha, 2018. "Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time," Management Science, INFORMS, vol. 64(1), pages 453-473, January.
    12. John Boudreau & Wallace Hopp & John O. McClain & L. Joseph Thomas, 2003. "On the Interface Between Operations and Human Resources Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 179-202, September.
    13. Jingqi Wang & Yong-Pin Zhou, 2018. "Impact of Queue Configuration on Service Time: Evidence from a Supermarket," Management Science, INFORMS, vol. 64(7), pages 3055-3075, July.
    14. David Knights & Darren McCabe, 1998. "‘What Happens when the Phone goes Wild?’: Staff, Stress and Spaces for Escape in a BPR Telephone Banking Work Regime," Journal of Management Studies, Wiley Blackwell, vol. 35(2), pages 163-194, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Diwas S. KC & Bradley R. Staats & Maryam Kouchaki & Francesca Gino, 2020. "Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Performance," Management Science, INFORMS, vol. 66(10), pages 4397-4416, October.
    2. Delasay, Mohammad & Ingolfsson, Armann & Kolfal, Bora & Schultz, Kenneth, 2019. "Load effect on service times," European Journal of Operational Research, Elsevier, vol. 279(3), pages 673-686.
    3. Smirnov, Dmitry & Huchzermeier, Arnd, 2020. "Analytics for labor planning in systems with load-dependent service times," European Journal of Operational Research, Elsevier, vol. 287(2), pages 668-681.
    4. Büşra Ergün‐Şahin & Evrim Didem Güneş & Ayşe Kocabıyıkoğlu & Ahmet Keskin, 2022. "How does workload affect test ordering behavior of physicians? An empirical investigation," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2664-2680, June.
    5. Maria R. Ibanez & Jonathan R. Clark & Robert S. Huckman & Bradley R. Staats, 2018. "Discretionary Task Ordering: Queue Management in Radiological Services," Management Science, INFORMS, vol. 64(9), pages 4389-4407, September.
    6. Hessam Bavafa & Lorin M. Hitt & Christian Terwiesch, 2018. "The Impact of E-Visits on Visit Frequencies and Patient Health: Evidence from Primary Care," Management Science, INFORMS, vol. 64(12), pages 5461-5480, December.
    7. Tom F. Tan & Bradley R. Staats, 2020. "Behavioral Drivers of Routing Decisions: Evidence from Restaurant Table Assignment," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 1050-1070, April.
    8. Mirko Kremer & Francis de Véricourt, 2022. "Mismanaging diagnostic accuracy under congestion," ESMT Research Working Papers ESMT-22-01, ESMT European School of Management and Technology.
    9. Sezer Ülkü & Chris Hydock & Shiliang Cui, 2022. "Social Queues (Cues): Impact of Others’ Waiting in Line on One’s Service Time," Management Science, INFORMS, vol. 68(11), pages 7958-7976, November.
    10. Wenhui Zhou & Dongmei Wang & Weixiang Huang & Pengfei Guo, 2021. "To Pool or Not to Pool? The Effect of Loss Aversion on Queue Configurations," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4258-4272, November.
    11. Choi, Yunsik & Delise, Lisa A. & Lee, Brandon W. & Neely, Jerry, 2021. "Effective staffing of projects for reconciling conflict between cost efficiency and quality," International Journal of Production Economics, Elsevier, vol. 234(C).
    12. Michael Freeman & Nicos Savva & Stefan Scholtes, 2017. "Gatekeepers at Work: An Empirical Analysis of a Maternity Unit," Management Science, INFORMS, vol. 63(10), pages 3147-3167, October.
    13. Masoud Kamalahmadi & Qiuping Yu & Yong-Pin Zhou, 2021. "Call to Duty: Just-in-Time Scheduling in a Restaurant Chain," Management Science, INFORMS, vol. 67(11), pages 6751-6781, November.
    14. Robert J. Batt & Christian Terwiesch, 2017. "Early Task Initiation and Other Load-Adaptive Mechanisms in the Emergency Department," Management Science, INFORMS, vol. 63(11), pages 3531-3551, November.
    15. Farzad Zaerpour & Marco Bijvank & Huiyin Ouyang & Zhankun Sun, 2022. "Scheduling of Physicians with Time‐Varying Productivity Levels in Emergency Departments," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 645-667, February.
    16. Mor Armony & Guillaume Roels & Hummy Song, 2021. "Pooling Queues with Strategic Servers: The Effects of Customer Ownership," Operations Research, INFORMS, vol. 69(1), pages 13-29, January.
    17. Carri W. Chan & Linda V. Green & Suparerk Lekwijit & Lijian Lu & Gabriel Escobar, 2019. "Assessing the Impact of Service Level When Customer Needs Are Uncertain: An Empirical Investigation of Hospital Step-Down Units," Management Science, INFORMS, vol. 65(2), pages 751-775, February.
    18. Jingqi Wang & Yong-Pin Zhou, 2018. "Impact of Queue Configuration on Service Time: Evidence from a Supermarket," Management Science, INFORMS, vol. 64(7), pages 3055-3075, July.
    19. Xu, Shuling & Hall, Nicholas G., 2021. "Fatigue, personnel scheduling and operations: Review and research opportunities," European Journal of Operational Research, Elsevier, vol. 295(3), pages 807-822.
    20. Jim G. Dai & Pengyi Shi, 2021. "Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1838-1862, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:68:y:2022:i:9:p:6697-6715. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.