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Inferring Balking Behavior From Transactional Data

Author

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  • Lee K. Jones

    (Department of Mathematical Sciences, University of Massachusetts, Lowell, Massachusetts 01854)

Abstract

Balking is the act of not joining a queue because the prospective arriving customer judges the queue to be too long. We analyze queues in the presence of balking, using only the service start and stop data utilized in Larson's Queue Inference Engine (Q.I.E.). Using an extension of Larson's congestion probability calculation to include balking we present new maximum likelihood, nonparametric, and Bayesian methods for inferring the arrival rate and balking functions. The methodology is applicable to businesses that wish to estimate lost sales because of balking arising from queuing-type congestion. The techniques are applied to a small transactional data set for illustrative purposes.

Suggested Citation

  • Lee K. Jones, 1999. "Inferring Balking Behavior From Transactional Data," Operations Research, INFORMS, vol. 47(5), pages 778-784, October.
    • Handle: RePEc:inm:oropre:v:47:y:1999:i:5:p:778-784
    DOI: 10.1287/opre.47.5.778
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    References listed on IDEAS

    as
    1. Richard C. Larson, 1991. "The Queue Inference Engine: Addendum," Management Science, INFORMS, vol. 37(8), pages 1062-1062, August.
    2. Richard C. Larson, 1990. "The Queue Inference Engine: Deducing Queue Statistics from Transactional Data," Management Science, INFORMS, vol. 36(5), pages 586-601, May.
    3. Lee K. Jones & Richard C. Larson, 1995. "Efficient Computation of Probabilities of Events Described by Order Statistics and Applications to Queue Inference," INFORMS Journal on Computing, INFORMS, vol. 7(1), pages 89-100, February.
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    Cited by:

    1. Azam Asanjarani & Yoni Nazarathy & Peter Taylor, 2021. "A survey of parameter and state estimation in queues," Queueing Systems: Theory and Applications, Springer, vol. 97(1), pages 39-80, February.

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