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Optimal Dynamic Pricing with Patient Customers

Author

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  • Yan Liu

    (Research Center for Management Science and Data Analytics, School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • William L. Cooper

    (Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

Abstract

We consider an infinite-horizon single-product pricing problem in which a fraction of customers is patient and the remaining fraction is impatient. A patient customer will wait up to some fixed number of time periods for the price of the product to fall below his or her valuation at which point the customer will make a purchase. If the price does not fall below a patient customer’s valuation at any time during those periods, then that customer will leave without buying. In contrast, impatient customers will not wait, and either buy immediately or leave without buying. We prove that there is an optimal dynamic pricing policy comprised of repeating cycles of decreasing prices. We obtain bounds on the length of these cycles, and we exploit these results to produce an efficient dynamic programming approach for computing such an optimal policy. We also consider problems in which customers have variable levels of patience. For such problems, cycles of decreasing prices may no longer be optimal, but numerical experiments nevertheless suggest that such a decreasing cyclic policy (suitably chosen) often performs quite well.

Suggested Citation

  • Yan Liu & William L. Cooper, 2015. "Optimal Dynamic Pricing with Patient Customers," Operations Research, INFORMS, vol. 63(6), pages 1307-1319, December.
  • Handle: RePEc:inm:oropre:v:63:y:2015:i:6:p:1307-1319
    DOI: 10.1287/opre.2015.1438
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    References listed on IDEAS

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    Cited by:

    1. Ilan Lobel, 2020. "Technical Note—Dynamic Pricing with Heterogeneous Patience Levels," Operations Research, INFORMS, vol. 68(4), pages 1038-1046, July.
    2. Victor F. Araman & Bassam Fayad, 2021. "Intertemporal Price Discrimination with Time-Varying Valuations," Operations Research, INFORMS, vol. 69(1), pages 245-265, January.
    3. Yiwei Chen & Vivek F. Farias & Nikolaos Trichakis, 2019. "On the Efficacy of Static Prices for Revenue Management in the Face of Strategic Customers," Management Science, INFORMS, vol. 65(12), pages 5535-5555, December.
    4. René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
    5. Zhenyu Hu & Xin Chen & Peng Hu, 2016. "Technical Note—Dynamic Pricing with Gain-Seeking Reference Price Effects," Operations Research, INFORMS, vol. 64(1), pages 150-157, February.
    6. Zizhuo Wang, 2016. "Technical Note—Intertemporal Price Discrimination via Reference Price Effects," Operations Research, INFORMS, vol. 64(2), pages 290-296, April.
    7. Yanan Song & Xiaobo Zhao, 2017. "A newsvendor problem with boundedly rational strategic customers," International Journal of Production Research, Taylor & Francis Journals, vol. 55(1), pages 228-243, January.
    8. Yiwei Chen & Cong Shi, 2019. "Joint Pricing and Inventory Management with Strategic Customers," Operations Research, INFORMS, vol. 67(6), pages 1610-1627, November.
    9. Yiwei Chen & Ming Hu, 2020. "Pricing and Matching with Forward-Looking Buyers and Sellers," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 717-734, July.
    10. Gökgür, Burak & Karabatı, Selçuk, 2019. "Dynamic and targeted bundle pricing of two independently valued products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 184-198.
    11. Yiwei Chen & Vivek F. Farias, 2018. "Robust Dynamic Pricing with Strategic Customers," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1119-1142, November.
    12. Doan, Xuan Vinh & Lei, Xiao & Shen, Siqian, 2020. "Pricing of reusable resources under ambiguous distributions of demand and service time with emerging applications," European Journal of Operational Research, Elsevier, vol. 282(1), pages 235-251.
    13. René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
    14. S. Srivatsa Srinivas & Rahul R. Marathe, 2020. "Equilibrium in a finite capacity M/M/1 queue with unknown service rates consisting of strategic and non-strategic customers," Queueing Systems: Theory and Applications, Springer, vol. 96(3), pages 329-356, December.
    15. Ioannis Stamatopoulos & Naveed Chehrazi & Achal Bassamboo, 2019. "Welfare Implications of Inventory-Driven Dynamic Pricing," Management Science, INFORMS, vol. 65(12), pages 5741-5765, December.

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