IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v63y2016i6p460-478.html
   My bibliography  Save this article

Stochastic call center staffing with uncertain arrival, service and abandonment rates: A Bayesian perspective

Author

Listed:
  • Tevfik Aktekin
  • Tahir Ekin

Abstract

In this article, we introduce staffing strategies for the Erlang‐A queuing system in call center operations with uncertain arrival, service, and abandonment rates. In doing so, we model the system rates using gamma distributions that create randomness in operating characteristics used in the optimization formulation. We divide the day into discrete time intervals where a simulation based stochastic programming method is used to determine staffing levels. More specifically, we develop a model to select the optimal number of agents required for a given time interval by minimizing an expected cost function, which consists of agent and abandonment (opportunity) costs, while considering the service quality requirements such as the delay probability. The objective function as well as the constraints in our formulation are random variables. The novelty of our approach is to introduce a solution method for the staffing of an operation where all three system rates (arrival, service, and abandonment) are random variables. We illustrate the use of the proposed model using both real and simulated call center data. In addition, we provide solution comparisons across different formulations, consider a dynamic extension, and discuss sensitivity implications of changing constraint upper bounds as well as prior hyper‐parameters. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 460–478, 2016

Suggested Citation

  • Tevfik Aktekin & Tahir Ekin, 2016. "Stochastic call center staffing with uncertain arrival, service and abandonment rates: A Bayesian perspective," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(6), pages 460-478, September.
    • Handle: RePEc:wly:navres:v:63:y:2016:i:6:p:460-478
    DOI: 10.1002/nav.21716
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.21716
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.21716?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. Linda Green & Peter Kolesar, 1991. "The Pointwise Stationary Approximation for Queues with Nonstationary Arrivals," Management Science, INFORMS, vol. 37(1), pages 84-97, January.
    2. Zeynep Akşin & Barış Ata & Seyed Morteza Emadi & Che-Lin Su, 2013. "Structural Estimation of Callers' Delay Sensitivity in Call Centers," Management Science, INFORMS, vol. 59(12), pages 2727-2746, December.
    3. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2009. "Pointwise Stationary Fluid Models for Stochastic Processing Networks," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 70-89, August.
    4. Tevfik Aktekin & Refik Soyer, 2012. "Bayesian analysis of queues with impatient customers: Applications to call centers," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(6), pages 441-456, September.
    5. Itay Gurvich & Mor Armony & Avishai Mandelbaum, 2008. "Service-Level Differentiation in Call Centers with Fully Flexible Servers," Management Science, INFORMS, vol. 54(2), pages 279-294, February.
    6. Peter Muller & Bruno Sanso & Maria De Iorio, 2004. "Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 788-798, January.
    7. Ety Zohar & Avishai Mandelbaum & Nahum Shimkin, 2002. "Adaptive Behavior of Impatient Customers in Tele-Queues: Theory and Empirical Support," Management Science, INFORMS, vol. 48(4), pages 566-583, April.
    8. 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.
    9. Tevfik Aktekin & Refik Soyer, 2011. "Call center arrival modeling: A Bayesian state‐space approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(1), pages 28-42, February.
    10. Landon, Joshua & Ruggeri, Fabrizio & Soyer, Refik & Murat Tarimcilar, M., 2010. "Modeling latent sources in call center arrival data," European Journal of Operational Research, Elsevier, vol. 204(3), pages 597-603, August.
    11. Ward Whitt, 2007. "What you should know about queueing models to set staffing requirements in service systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(5), pages 476-484, August.
    12. Concha Bielza & Peter Müller & David Ríos Insua, 1999. "Decision Analysis by Augmented Probability Simulation," Management Science, INFORMS, vol. 45(7), pages 995-1007, July.
    13. Itai Gurvich & James Luedtke & Tolga Tezcan, 2010. "Staffing Call Centers with Uncertain Demand Forecasts: A Chance-Constrained Optimization Approach," Management Science, INFORMS, vol. 56(7), pages 1093-1115, July.
    14. Tahir Ekin & Nicholas G. Polson & Refik Soyer, 2014. "Augmented Markov Chain Monte Carlo Simulation for Two-Stage Stochastic Programs with Recourse," Decision Analysis, INFORMS, vol. 11(4), pages 250-264, December.
    15. Martin Pincus, 1970. "Letter to the Editor—A Monte Carlo Method for the Approximate Solution of Certain Types of Constrained Optimization Problems," Operations Research, INFORMS, vol. 18(6), pages 1225-1228, December.
    16. Kirschenmann, Thomas & Popova, Elmira & Damien, Paul & Hanson, Tim, 2014. "Decision dependent stochastic processes," European Journal of Operational Research, Elsevier, vol. 234(3), pages 731-742.
    17. Lawrence Brown & Noah Gans & Avishai Mandelbaum & Anat Sakov & Haipeng Shen & Sergey Zeltyn & Linda Zhao, 2005. "Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 36-50, March.
    18. Weinberg, Jonathan & Brown, Lawrence D. & Stroud, Jonathan R., 2007. "Bayesian Forecasting of an Inhomogeneous Poisson Process With Applications to Call Center Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1185-1198, December.
    19. Oualid Jouini & Zeynep Akşin & Yves Dallery, 2011. "Call Centers with Delay Information: Models and Insights," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 534-548, October.
    20. Haipeng Shen & Jianhua Z. Huang, 2008. "Interday Forecasting and Intraday Updating of Call Center Arrivals," Manufacturing & Service Operations Management, INFORMS, vol. 10(3), pages 391-410, July.
    21. Júlíus Atlason & Marina A. Epelman & Shane G. Henderson, 2008. "Optimizing Call Center Staffing Using Simulation and Analytic Center Cutting-Plane Methods," Management Science, INFORMS, vol. 54(2), pages 295-309, February.
    22. Oualid Jouini & Zeynep Aksin & Yves Dallery, 2011. "Call Centers with Delay Information: Models and Insights," Post-Print hal-00680769, HAL.
    23. Avishai Mandelbaum & Sergey Zeltyn, 2009. "Staffing Many-Server Queues with Impatient Customers: Constraint Satisfaction in Call Centers," Operations Research, INFORMS, vol. 57(5), pages 1189-1205, October.
    24. Jacquier, Eric & Johannes, Michael & Polson, Nicholas, 2007. "MCMC maximum likelihood for latent state models," Journal of Econometrics, Elsevier, vol. 137(2), pages 615-640, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huidong Zhang & Dragan Djurdjanovic, 2022. "Integrated production and maintenance planning under uncertain demand with concurrent learning of yield rate," Flexible Services and Manufacturing Journal, Springer, vol. 34(2), pages 429-450, June.
    2. Ekin, Tahir & Aktekin, Tevfik, 2021. "Decision making under uncertain and dependent system rates in service systems," European Journal of Operational Research, Elsevier, vol. 291(1), pages 335-348.
    3. Tahir Ekin & Stephen Walker & Paul Damien, 2023. "Augmented simulation methods for discrete stochastic optimization with recourse," Annals of Operations Research, Springer, vol. 320(2), pages 771-793, January.
    4. Kaan Kuzu & Refik Soyer, 2018. "Bayesian modeling of abandonments in ticket queues," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(6-7), pages 499-521, September.
    5. Hani Amir Aouissi & Ahmed Hamimes & Mostefa Ababsa & Lavinia Bianco & Christian Napoli & Feriel Kheira Kebaili & Andrey E. Krauklis & Hafid Bouzekri & Kuldeep Dhama, 2022. "Bayesian Modeling of COVID-19 to Classify the Infection and Death Rates in a Specific Duration: The Case of Algerian Provinces," IJERPH, MDPI, vol. 19(15), pages 1-18, August.
    6. Tahir Ekin & Nicholas G. Polson & Refik Soyer, 2017. "Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 613-627, December.
    7. Ekin, Tahir, 2018. "Integrated maintenance and production planning with endogenous uncertain yield," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 52-61.

    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. Ekin, Tahir & Aktekin, Tevfik, 2021. "Decision making under uncertain and dependent system rates in service systems," European Journal of Operational Research, Elsevier, vol. 291(1), pages 335-348.
    2. Itai Gurvich & James Luedtke & Tolga Tezcan, 2010. "Staffing Call Centers with Uncertain Demand Forecasts: A Chance-Constrained Optimization Approach," Management Science, INFORMS, vol. 56(7), pages 1093-1115, July.
    3. Kaan Kuzu & Refik Soyer, 2018. "Bayesian modeling of abandonments in ticket queues," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(6-7), pages 499-521, September.
    4. Merve Bodur & James R. Luedtke, 2017. "Mixed-Integer Rounding Enhanced Benders Decomposition for Multiclass Service-System Staffing and Scheduling with Arrival Rate Uncertainty," Management Science, INFORMS, vol. 63(7), pages 2073-2091, July.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Ekin, Tahir, 2018. "Integrated maintenance and production planning with endogenous uncertain yield," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 52-61.
    7. Noah Gans & Haipeng Shen & Yong-Pin Zhou & Nikolay Korolev & Alan McCord & Herbert Ristock, 2015. "Parametric Forecasting and Stochastic Programming Models for Call-Center Workforce Scheduling," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 571-588, October.
    8. Kinshuk Jerath & Anuj Kumar & Serguei Netessine, 2015. "An Information Stock Model of Customer Behavior in Multichannel Customer Support Services," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 368-383, July.
    9. 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.
    10. Boris N. Oreshkin & Nazim Réegnard & Pierre L’Ecuyer, 2016. "Rate-Based Daily Arrival Process Models with Application to Call Centers," Operations Research, INFORMS, vol. 64(2), pages 510-527, April.
    11. Tahir Ekin & Nicholas G. Polson & Refik Soyer, 2017. "Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 613-627, December.
    12. Zeynep Akşin & Barış Ata & Seyed Morteza Emadi & Che-Lin Su, 2013. "Structural Estimation of Callers' Delay Sensitivity in Call Centers," Management Science, INFORMS, vol. 59(12), pages 2727-2746, December.
    13. Junfei Huang & Avishai Mandelbaum & Hanqin Zhang & Jiheng Zhang, 2017. "Refined Models for Efficiency-Driven Queues with Applications to Delay Announcements and Staffing," Operations Research, INFORMS, vol. 65(5), pages 1380-1397, October.
    14. Robert J. Batt & Christian Terwiesch, 2015. "Waiting Patiently: An Empirical Study of Queue Abandonment in an Emergency Department," Management Science, INFORMS, vol. 61(1), pages 39-59, January.
    15. Ibrahim, Rouba & Ye, Han & L’Ecuyer, Pierre & Shen, Haipeng, 2016. "Modeling and forecasting call center arrivals: A literature survey and a case study," International Journal of Forecasting, Elsevier, vol. 32(3), pages 865-874.
    16. Barrow, Devon K., 2016. "Forecasting intraday call arrivals using the seasonal moving average method," Journal of Business Research, Elsevier, vol. 69(12), pages 6088-6096.
    17. Ran Liu & Xiaolan Xie, 2018. "Physician Staffing for Emergency Departments with Time-Varying Demand," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 588-607, August.
    18. Robbins, Thomas R. & Harrison, Terry P., 2010. "A stochastic programming model for scheduling call centers with global Service Level Agreements," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1608-1619, December.
    19. Zeynep Akşin & Baris Ata & Seyed Morteza Emadi & Che-Lin Su, 2017. "Impact of Delay Announcements in Call Centers: An Empirical Approach," Operations Research, INFORMS, vol. 65(1), pages 242-265, February.
    20. Aktekin, Tevfik, 2014. "Call center service process analysis: Bayesian parametric and semi-parametric mixture modeling," European Journal of Operational Research, Elsevier, vol. 234(3), pages 709-719.

    More about this item

    Statistics

    Access and download statistics

    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:wly:navres:v:63:y:2016:i:6:p:460-478. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.