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Intertemporal Pricing Under Minimax Regret

Author

Listed:
  • René Caldentey

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

  • Ying Liu

    (Stern School of Business, New York University, New York, New York 10012)

  • Ilan Lobel

    (Stern School of Business, New York University, New York, New York 10012)

Abstract

We consider the pricing problem faced by a monopolist who sells a product to a population of consumers over a finite time horizon. Customers’ types differ along two dimensions: (i) their willingness-to-pay for the product and (ii) their arrival time during the selling season. We assume that the seller knows only the support of the customers’ valuations and do not make any other distributional assumptions about customers’ willingness-to-pay or arrival times. We consider a robust formulation of the seller’s pricing problem that is based on the minimization of her worst-case regret. We consider two distinct cases of customers’ purchasing behavior: myopic and strategic customers. For both of these cases, we characterize optimal price paths. For myopic customers, the regret is determined by the price at a critical time. Depending on the problem parameters, this critical time will be either the end of the selling season or it will be a time that equalizes the worst-case regret generated by undercharging customers and the worst-case regret generated by customers waiting for the price to fall. The optimal pricing strategy is not unique except at the critical time. For strategic consumers, we develop a robust mechanism design approach to compute an optimal policy. Depending on the problem parameters, the optimal policy might lead some consumers to wait until the end of the selling season and might price others out of the market. Under strategic customers, the optimal price equalizes the regrets generated by different customer types that arrive at the beginning of the selling season. We show that a seller that does not know if the customers are myopic should price as if they are strategic. We also show there is no benefit under myopic consumers to having a selling season longer than a certain uniform bound, but that the same is not true with strategic consumers.

Suggested Citation

  • René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
  • Handle: RePEc:inm:oropre:v:65:y:2017:i:1:p:104-129
    DOI: 10.1287/opre.2016.1548
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    5. Thomas A. Weber, 2023. "Relatively robust decisions," Theory and Decision, Springer, vol. 94(1), pages 35-62, January.
    6. Han, Jun & Weber, Thomas A., 2023. "Price discrimination with robust beliefs," European Journal of Operational Research, Elsevier, vol. 306(2), pages 795-809.
    7. Tommi Ekholm & Erin Baker, 2022. "Multiple Beliefs, Dominance and Dynamic Consistency," Management Science, INFORMS, vol. 68(1), pages 529-540, January.
    8. Wang, Wei & Lan, Yingjie, 2022. "Robust one-way trading with limited number of transactions and heuristics for fixed transaction costs," International Journal of Production Economics, Elsevier, vol. 247(C).
    9. Mengshi Lu & Zuo‐Jun Max Shen, 2021. "A Review of Robust Operations Management under Model Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1927-1943, June.
    10. Xu, Xiaoyan & Choi, Tsan-Ming & Chung, Sai-Ho & Guo, Shu, 2023. "Collaborative-commerce in supply chains: A review and classification of analytical models," International Journal of Production Economics, Elsevier, vol. 263(C).
    11. Mustafa O. Kabul & Ali K. Parlaktürk, 2019. "The Value of Commitments When Selling to Strategic Consumers: A Supply Chain Perspective," Management Science, INFORMS, vol. 65(10), pages 4754-4770, October.
    12. Fuqiang Zhang & Renyu Zhang, 2018. "Trade-in Remanufacturing, Customer Purchasing Behavior, and Government Policy," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 601-616, October.
    13. Zhang, Guoquan & Li, Guohao & Shang, Jennifer, 2023. "Optimizing mixed bundle pricing strategy: Advance selling and consumer regret," Omega, Elsevier, vol. 115(C).
    14. Zhi Chen & Weijun Xie, 2021. "Regret in the Newsvendor Model with Demand and Yield Randomness," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4176-4197, November.
    15. Qiu, Ruozhen & Sun, Yue & Zhou, Hongcheng & Sun, Minghe, 2023. "Dynamic pricing and quick response of a retailer in the presence of strategic consumers: A distributionally robust optimization approach," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1270-1298.
    16. Shixin Wang, 2023. "The Power of Simple Menus in Robust Selling Mechanisms," Papers 2310.17392, arXiv.org, revised Sep 2024.
    17. Shixin Wang, 2024. "Semi-Separable Mechanisms in Multi-Item Robust Screening," Papers 2408.13580, arXiv.org.
    18. Ken Moon & Kostas Bimpikis & Haim Mendelson, 2018. "Randomized Markdowns and Online Monitoring," Management Science, INFORMS, vol. 64(3), pages 1271-1290, March.
    19. Wanchang Zhang, 2022. "Auctioning Multiple Goods without Priors," Papers 2204.13726, arXiv.org.
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