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Sensitivity of optimal prices to system parameters in a steady-state service facility

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  • Aktaran-KalaycI, Tûba
  • Ayhan, Hayriye

Abstract

We consider the problem of maximizing the long-run average reward in a service facility with dynamic pricing. We investigate sensitivity of optimal pricing policies to the parameters of the service facility which is modelled as an M/M/s/K queueing system. Arrival process to the facility is Poisson with arrival rate a decreasing function of the price currently being charged by the facility. We prove structural results on the optimal pricing policies when the parameters in the facility change. Namely, we show that optimal prices decrease when the capacity of the facility or the number of servers in the facility increase. Under a reasonable assumption, we also show that optimal prices increase as the overall demand for the service provided by the facility increases or when the service rate of the facility decreases. We illustrate how these structural results simplify the required computational effort while finding the optimal policy.

Suggested Citation

  • Aktaran-KalaycI, Tûba & Ayhan, Hayriye, 2009. "Sensitivity of optimal prices to system parameters in a steady-state service facility," European Journal of Operational Research, Elsevier, vol. 193(1), pages 120-128, February.
  • Handle: RePEc:eee:ejores:v:193:y:2009:i:1:p:120-128
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    References listed on IDEAS

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    Cited by:

    1. Xinchang Wang & Sigrún Andradóttir & Hayriye Ayhan, 2019. "Optimal pricing for tandem queues with finite buffers," Queueing Systems: Theory and Applications, Springer, vol. 92(3), pages 323-396, August.
    2. A. Baykal Hafızoğlu & Esma S. Gel & Pınar Keskinocak, 2016. "Price and Lead Time Quotation for Contract and Spot Customers," Operations Research, INFORMS, vol. 64(2), pages 406-415, April.
    3. Secil Savasaneril & Ece Sayin, 2017. "Dynamic lead time quotation under responsive inventory and multiple customer classes," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 95-135, January.
    4. Seçil Savaşaneril & Paul M. Griffin & Pınar Keskinocak, 2010. "Dynamic Lead-Time Quotation for an M/M/1 Base-Stock Inventory Queue," Operations Research, INFORMS, vol. 58(2), pages 383-395, April.
    5. Demet Batur & Jennifer K. Ryan & Zhongyuan Zhao & Mehmet C. Vuran, 2019. "Dynamic Pricing of Wireless Internet Based on Usage and Stochastically Changing Capacity," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 833-852, October.
    6. Samuel Vercraene & Jean-Philippe Gayon & Fikri Karaesmen, 2018. "Effects of System Parameters on the Optimal Cost and Policy in a Class of Multidimensional Queueing Control Problems," Operations Research, INFORMS, vol. 66(1), pages 150-162, January.

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