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Service Competition with General Queueing Facilities

Author

Listed:
  • Gad Allon

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208)

  • Awi Federgruen

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

Abstract

In many service industries, companies compete with each other on the basis of the waiting time their customers experience, along with the price they charge for their service. A firm's waiting-time standard may either be defined in terms of the expected value or a given, for example 95%, percentile of the steady state waiting-time distribution. We investigate how a service industry's competitive behavior depends on the characteristics of the service providers' queueing systems. We provide a unifying approach to investigate various standard single-stage systems covering the spectrum from M/M/1 to general G/GI/s systems, along with open Jackson networks to represent multistage service systems. Assuming that the capacity cost is proportional with the service rates, we refer to its dependence on (i) the firm's demand rate, and (ii) the waiting-time standard as the capacity cost function. We show that across the above broad spectrum of queueing models, the capacity cost function belongs to a specific four-parameter class of function, either exactly or as a close approximation. We then characterize how this capacity cost function impacts the equilibrium behavior in the industry. We give separate treatments to the case where the firms compete in terms of (i) prices (only), (ii) their service level or waiting-time standard (only), and (iii) simultaneously in terms of both prices and service levels. The firms' demand rates are given by a general system of equations of the prices and waiting-time standards in the industry.

Suggested Citation

  • Gad Allon & Awi Federgruen, 2008. "Service Competition with General Queueing Facilities," Operations Research, INFORMS, vol. 56(4), pages 827-849, August.
  • Handle: RePEc:inm:oropre:v:56:y:2008:i:4:p:827-849
    DOI: 10.1287/opre.1080.0545
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    References listed on IDEAS

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    Cited by:

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    2. Xuchuan Yuan & Tinglong Dai & Lucy Gongtao Chen & Srinagesh Gavirneni, 2021. "Co-Opetition in Service Clusters with Waiting-Area Entertainment," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 106-122, 1-2.
    3. Georgia Perakis & Wei Sun, 2014. "Efficiency Analysis of Cournot Competition in Service Industries with Congestion," Management Science, INFORMS, vol. 60(11), pages 2684-2700, November.
    4. Hongyan Li & Joern Meissner, 2018. "Capacity optimization and competition with cyclical and lead-time-dependent demands," Annals of Operations Research, Springer, vol. 271(2), pages 737-763, December.
    5. Nicos Savva & Tolga Tezcan & Özlem Yıldız, 2019. "Can Yardstick Competition Reduce Waiting Times?," Management Science, INFORMS, vol. 65(7), pages 3196-3215, July.
    6. Houyuan Jiang & Zhan Pang & Sergei Savin, 2020. "Performance Incentives and Competition in Health Care Markets," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1145-1164, May.
    7. Gad Allon & Awi Federgruen & Margaret Pierson, 2011. "How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 489-507, October.
    8. Giuseppe d'Acquisto & Patrick Maillé & Maurizio Naldi & Bruno Tuffin, 2012. "Impact on retail prices of non-neutral wholesale prices for content providers," Post-Print hal-00725050, HAL.
    9. Liu, Yan & Shi, Hongyan & Petruzzi, Nicholas C., 2018. "Optimal quality and quantity provisions for centralized vs. decentralized distribution: Market size uncertainty effects," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1144-1158.
    10. Delgado-Alvarez, Carlos A. & van Ackere, Ann & Larsen, Erik R & Arango-Aramburo, Santiago, 2017. "Managing capacity at a service facility: An experimental approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 216-228.
    11. Wang, Haiyan & Olsen, Tava Lennon & Liu, Guiqing, 2018. "Service capacity competition with peak arrivals and delay sensitive customers," Omega, Elsevier, vol. 77(C), pages 80-95.
    12. Tianhu Deng & Ying‐Ju Chen & Zuo‐Jun Max Shen, 2015. "Optimal pricing and scheduling control of product shipping," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(3), pages 215-227, April.
    13. Melo, Emerson, 2014. "Price competition, free entry, and welfare in congested markets," Games and Economic Behavior, Elsevier, vol. 83(C), pages 53-72.
    14. Houyuan Jiang & Zhan Pang & Sergei Savin, 2017. "Improving Patient Access to Care: Performance Incentives and Competition in Healthcare Markets," Working Papers 2017/01, Cambridge Judge Business School, University of Cambridge.
    15. Ramesh Johari & Gabriel Y. Weintraub & Benjamin Van Roy, 2010. "Investment and Market Structure in Industries with Congestion," Operations Research, INFORMS, vol. 58(5), pages 1303-1317, October.
    16. C. D’Apice & A. N. Dudin & O. S. Dudina & R. Manzo, 2024. "Analysis of Queueing System with Dynamic Rating-Dependent Arrival Process and Price of Service," Mathematics, MDPI, vol. 12(7), pages 1-20, April.

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