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Stalking the Endangered CAT: A Queueing Analysis of Congestion at Automatic Teller Machines

Author

Listed:
  • Peter Kolesar

    (Graduate School of Business, Uris Hall, Columbia University, New York, New York 10027)

Abstract

A study to determine customer service standards for the automatic teller machines (ATM's) of a large retail bank led to the formulation and calibration of a finite waiting room M / M / c / K queueing model. The model suggested that the percentage of lost customers be adopted as the service standard instead of line wait. The new standard was applied against existing transaction reports to identify those congested ATM facilities that could best profit from additional machines and lobby space. The magnitude of the increased business at the upgraded facilities partly confirmed the model's hypothesis that substantial numbers of customers had indeed been balking.

Suggested Citation

  • Peter Kolesar, 1984. "Stalking the Endangered CAT: A Queueing Analysis of Congestion at Automatic Teller Machines," Interfaces, INFORMS, vol. 14(6), pages 16-26, December.
    • Handle: RePEc:inm:orinte:v:14:y:1984:i:6:p:16-26
    DOI: 10.1287/inte.14.6.16
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    Cited by:

    1. Reza Aghajani & Kavita Ramanan, 2020. "The Limit of Stationary Distributions of Many-Server Queues in the Halfin–Whitt Regime," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 1016-1055, August.
    2. Qian Wang & Rajan Batta & Christopher M. Rump, 2004. "Facility location models for immobile servers with stochastic demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(1), pages 137-152, February.
    3. Tan, Xiaoqian & Knessl, Charles & Yang, Yongzhi (Peter), 2013. "On finite capacity queues with time dependent arrival rates," Stochastic Processes and their Applications, Elsevier, vol. 123(6), pages 2175-2227.
    4. 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.

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