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Technical Note---A Risk-Sensitive Model for Managing Perishable Products

Author

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  • Youyi Feng

    (Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong)

  • Baichun Xiao

    (Department of Management, Long Island University, C.W. Post, Brookville, New York 11548, and School of Economics and Management, Southwest Jiaotong University, Chengdu, 610031, China)

Abstract

This article presents a risk-sensitive model for managing perishable products assuming the supplier is averse to the variation of revenues. While traditional risk-neutral revenue management models offer optimal strategies in the long run, they are exposed to the variation of revenue flows. If a short-term revenue target is a primary concern for the supplier, the risk-neutral assumption fails to provide the best policy needed. The proposed model uses an exponential function with a risk-sensitive parameter instead of the conventional risk-neutral objective. The risk parameter measures how the supplier is sensitive to the deviation of revenues. We show that the new objective function captures the supplier's risk behavior. We develop a recursive procedure for the optimal solution in closed form. The optimal policy has attractive properties such as nested active price set, monotonicity with respect to the remaining time and inventory, and threshold-type control. When the supplier is more sensitive to the uncertain revenue flows, the risk-sensitive model leads to more conservative pricing policies. Finally, we show that the risk-neutral model is a special case of the proposed framework.

Suggested Citation

  • Youyi Feng & Baichun Xiao, 2008. "Technical Note---A Risk-Sensitive Model for Managing Perishable Products," Operations Research, INFORMS, vol. 56(5), pages 1305-1311, October.
  • Handle: RePEc:inm:oropre:v:56:y:2008:i:5:p:1305-1311
    DOI: 10.1287/opre.1080.0561
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    References listed on IDEAS

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    1. Andrew E. B. Lim & J. George Shanthikumar, 2007. "Relative Entropy, Exponential Utility, and Robust Dynamic Pricing," Operations Research, INFORMS, vol. 55(2), pages 198-214, April.
    2. W. H. Fleming & S. J. Sheu, 2000. "Risk‐Sensitive Control and an Optimal Investment Model," Mathematical Finance, Wiley Blackwell, vol. 10(2), pages 197-213, April.
    3. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
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    Cited by:

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    2. Terciyanlı, Erman & Avṣar, Zeynep Müge, 2019. "Alternative risk-averse approaches for airline network revenue management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 27-46.
    3. Catherine Cleophas & Daniel Kadatz & Sebastian Vock, 2017. "Resilient revenue management: a literature survey of recent theoretical advances," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(5), pages 483-498, October.
    4. Gönsch, Jochen, 2017. "A survey on risk-averse and robust revenue management," European Journal of Operational Research, Elsevier, vol. 263(2), pages 337-348.
    5. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    6. Sebastian Koch & Jochen Gönsch & Michael Hassler & Robert Klein, 2016. "Practical decision rules for risk-averse revenue management using simulation-based optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 468-487, December.
    7. Jochen Gönsch & Michael Hassler & Rouven Schur, 2018. "Optimizing conditional value-at-risk in dynamic pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 711-750, July.
    8. Rainer Schlosser, 2016. "Stochastic dynamic multi-product pricing with dynamic advertising and adoption effects," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(2), pages 153-169, April.

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