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Strategic customer behavior in a queueing system with alternating information structure

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  • Dimitrakopoulos, Yiannis
  • Economou, Antonis
  • Leonardos, Stefanos

Abstract

Strategic customer behavior is strongly influenced by the level of information that is provided to customers. Hence, to optimize the design of queueing systems, many studies consider various versions of the same service model and compare them under different information structures. In particular, two extreme versions are usually considered and compared: the observable in which customers are informed about the number of customers in the system and the unobservable in which they are only informed about the system parameters, e.g., arrival and service rates. In the present work, we study a model that bridges these two versions. More concretely, we assume that the system alternates between observable and unobservable periods. We characterize and compute customer equilibrium joining/balking strategies and show that the present model unifies and extends existing approaches of both heterogeneously observable models and models with delayed observations. More importantly, our findings indicate that an alternating information structure implies in general higher equilibrium throughput and social welfare in comparison to both the observable and unobservable cases. We complement our results with numerical experiments and provide managerial insight on the optimal control of the system parameters.

Suggested Citation

  • Dimitrakopoulos, Yiannis & Economou, Antonis & Leonardos, Stefanos, 2021. "Strategic customer behavior in a queueing system with alternating information structure," European Journal of Operational Research, Elsevier, vol. 291(3), pages 1024-1040.
    • Handle: RePEc:eee:ejores:v:291:y:2021:i:3:p:1024-1040
    DOI: 10.1016/j.ejor.2020.10.054
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    Citations

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    Cited by:

    1. Siddharth Prakash Singh & Mohammad Delasay & Alan Scheller‐Wolf, 2023. "Real‐time delay announcement under competition," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 863-881, March.
    2. Tunçalp, Feray & Güneş, Evrim D. & Örmeci, E. Lerzan, 2024. "Modeling strategic walk-in patients in appointment systems: Equilibrium behavior and capacity allocation," European Journal of Operational Research, Elsevier, vol. 313(2), pages 587-601.
    3. Antonis Economou, 2022. "How much information should be given to the strategic customers of a queueing system?," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 421-423, April.
    4. Antonio Di Crescenzo & Barbara Martinucci & Paola Paraggio, 2023. "Vessels Arrival Process and its Application to the SHIP/M/ $$\infty$$ ∞ Queue," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-33, March.
    5. İşlier, Zeynep Gökçe & Güllü, Refik, 2024. "On strategic customers with correlated utility attributes: Effects and information benefits," European Journal of Operational Research, Elsevier, vol. 313(1), pages 258-269.

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