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Structural properties of Markov modulated revenue management problems

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  • Özkan, Can
  • Karaesmen, Fikri
  • Özekici, Süleyman
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    Abstract

    The admission decision is one of the fundamental categories of demand-management decisions. In the dynamic model of the single-resource capacity control problem, the distribution of demand does not explicitly depend on external conditions. However, in reality, demand may depend on the current external environment which represents the prevailing economic, financial, social or other factors that affect customer behavior. We formulate a Markov Decision Process (MDP) to maximize expected revenues over a finite horizon that explicitly models the current environment. We derive some structural results of the optimal admission policy, including the existence of an environment-dependent thresholds and a comparison of threshold levels in different environments. We also present some computational results which illustrate these structural properties. Finally, we extend some of the results to a related dynamic pricing formulation.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 225 (2013)
    Issue (Month): 2 ()
    Pages: 324-331

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    Handle: RePEc:eee:ejores:v:225:y:2013:i:2:p:324-331

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Revenue management; Dynamic programming; Markov modulation;

    References

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    1. C. Barz & K. Waldmann, 2007. "Risk-sensitive capacity control in revenue management," Computational Statistics, Springer, vol. 65(3), pages 565-579, June.
    2. Eren Çil & E. Örmeci & Fikri Karaesmen, 2007. "Structural results on a batch acceptance problem for capacitated queues," Computational Statistics, Springer, vol. 66(2), pages 263-274, October.
    3. \c{S}. \.Ilker Birbil & J. B. G. Frenk & Joaquim A. S. Gromicho & Shuzhong Zhang, 2009. "The Role of Robust Optimization in Single-Leg Airline Revenue Management," Management Science, INFORMS, vol. 55(1), pages 148-163, January.
    4. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    5. Yingjie Lan & Huina Gao & Michael O. Ball & Itir Karaesmen, 2008. "Revenue Management with Limited Demand Information," Management Science, INFORMS, vol. 54(9), pages 1594-1609, September.
    6. Keilson, Julian & Kester, Adri, 1977. "Monotone matrices and monotone Markov processes," Stochastic Processes and their Applications, Elsevier, vol. 5(3), pages 231-241, July.
    7. Arifoglu, Kenan & Özekici, Süleyman, 2010. "Optimal policies for inventory systems with finite capacity and partially observed Markov-modulated demand and supply processes," European Journal of Operational Research, Elsevier, vol. 204(3), pages 421-438, August.
    8. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
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    Cited by:
    1. Chen, Jing & Wang, Jian & Bell, Peter C., 2014. "Lease expiration management for a single lease term in the apartment industry," European Journal of Operational Research, Elsevier, vol. 238(1), pages 233-244.

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