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Strategic Experimentation in Queues

Author

Listed:
  • Caroline D. Thomas

    (Department of Economics, The University of Texas at Austin)

  • Martin W. Cripps

    (Department of Economics, University College London)

Abstract

We analyze the social and private learning at the symmetric equilibria of a queueing game with strategic experimentation. An infinite sequence of agents arrive at a server which processes them at an unknown rate. The number of agents served at each date is either: a geometric random variable in the good state, or zero in the bad state. The queue lengthens with each new arrival and shortens if the agents are served or choose to quit the queue. Agents can only observe the evolution of the queue after they arrive, thus each agent solves the experimentation problem of how long to wait to learn about the probability of service. The agents, in addition, benefit from an informational externality by observing the length of the queue and the actions of other agents. There is also a negative payoff externality as those at the front of the queue delay the service of those at the back.

Suggested Citation

  • Caroline D. Thomas & Martin W. Cripps, "undated". "Strategic Experimentation in Queues," Department of Economics Working Papers 140228, The University of Texas at Austin, Department of Economics, revised Sep 2016.
    • Handle: RePEc:tex:wpaper:140228
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    File URL: https://sites.google.com/site/carotho14/research/files/queues160903.pdf
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    References listed on IDEAS

    as
    1. Caroline D. Thomas, 2021. "Strategic Experimentation with Congestion," American Economic Journal: Microeconomics, American Economic Association, vol. 13(1), pages 1-82, February.
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    Cited by:

    1. Monzón, Ignacio, 2019. "Observational learning in large anonymous games," Theoretical Economics, Econometric Society, vol. 14(2), May.
    2. Eyster, Erik & Galeotti, Andrea & Kartik, Navin & Rabin, Matthew, 2014. "Congested observational learning," Games and Economic Behavior, Elsevier, vol. 87(C), pages 519-538.
    3. Eeva Mauring, 2020. "Informational Cycles in Search Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 12(4), pages 170-192, November.
    4. Eeva Mauring, 2020. "Informational Cycles in Search Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 12(4), pages 170-192, November.
    5. Zhang, Min, 2021. "Non-monotone social learning," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 565-579.
    6. Hung Q. Nguyen & Tuan Phung-Duc, 2022. "Strategic customer behavior and optimal policies in a passenger–taxi double-ended queueing system with multiple access points and nonzero matching times," Queueing Systems: Theory and Applications, Springer, vol. 102(3), pages 481-508, December.

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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