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Optimal Pricing of Seasonal Products in the Presence of Forward-Looking Consumers

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  • Yossi Aviv

    ()
    (Olin School of Business, Washington University, St. Louis, Missouri 63130)

  • Amit Pazgal

    ()
    (Jesse H. Jones Graduate School of Management, Rice University, Houston, Texas 77252)

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    Abstract

    We study the optimal pricing of a finite quantity of a fashion-like seasonal good in the presence of forward-looking (strategic) customers. We distinguish between two classes of pricing strategies: contingent and announced fixed-discount. In both cases, the seller acts as a Stackelberg leader announcing his pricing strategy, while consumers act as followers taking the seller's strategy as given and determining their purchasing behavior. In each case, we identify a subgame-perfect Nash equilibrium and show that given the seller's strategy, the equilibrium in the consumer subgame is unique and consists of symmetric threshold purchasing policies. For both cases, we develop a benchmark model in which customers are nonstrategic (myopic). We conduct a comprehensive numerical study to explore the impact of strategic consumer behavior on pricing policies and expected revenue performance. We show that strategic customer behavior suppresses the benefits of price segmentation, particularly under medium-to-high values of heterogeneity and modest rates of decline in valuations. However, when the level of consumer heterogeneity is small, the rate of decline is medium-to-high, and the seller can optimally choose the time of discount in advance, segmentation can be used quite effectively even with strategic consumers. We find that the seller cannot avoid the adverse impact of strategic consumer behavior even under low levels of initial inventory. We argue that while the seller expects customers to be more concerned about product availability at discount time, he cannot use high-price "betting" strategies as he would in the case of low inventory and myopic customers. Under certain qualifications, announced fixed-discount strategies perform essentially the same as contingent pricing policies in the case of myopic consumers. However, under strategic consumer behavior, announced pricing policies can be advantageous to the seller, compared to contingent pricing schemes. Interestingly, those cases that announced discount strategies offer a significant advantage compared to contingent pricing policies. They appear to offer only a minimal advantage in comparison to fixed-pricing policies. Finally, when the seller incorrectly assumes that strategic customers are myopic in their purchasing decisions, it can be quite costly, reaching potential revenue losses of about 20%.

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    File URL: http://dx.doi.org/10.1287/msom.1070.0183
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    Bibliographic Info

    Article provided by INFORMS in its journal Manufacturing & Service Operations Management.

    Volume (Year): 10 (2008)
    Issue (Month): 3 (December)
    Pages: 339-359

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    Handle: RePEc:inm:ormsom:v:10:y:2008:i:3:p:339-359

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    Related research

    Keywords: dynamic pricing; game theory applications; marketing-operations interface; revenue management; strategic consumer behavior;

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    Cited by:
    1. Mantin, Benny & Gillen, David, 2011. "The hidden information content of price movements," European Journal of Operational Research, Elsevier, vol. 211(2), pages 385-393, June.
    2. Dirk Bergemann & Maher Said, 2010. "Dynamic Auctions: A Survey," Levine's Working Paper Archive 661465000000000111, David K. Levine.
    3. Anily, Shoshana & Hassin, Refael, 2013. "Pricing, replenishment, and timing of selling in a market with heterogeneous customers," International Journal of Production Economics, Elsevier, vol. 145(2), pages 672-682.
    4. Johannes Horner & Larry Samuelson, 2009. "Managing Strategic Buyers," Levine's Working Paper Archive 814577000000000059, David K. Levine.
    5. Kuo, Chia-Wei & Huang, Kwei-Long, 2012. "Dynamic pricing of limited inventories for multi-generation products," European Journal of Operational Research, Elsevier, vol. 217(2), pages 394-403.
    6. Mohammad Ali Kashefi, 2013. "The Effect of Salvage Market on Strategic Technology Choice and Capacity Investment Decision of Firm under Demand Uncertainty," Iranian Economic Review, Economics faculty of Tehran university, vol. 18(1), pages 25-67, winter.
    7. Choi, Tsan-Ming & Sethi, Suresh, 2010. "Innovative quick response programs: A review," International Journal of Production Economics, Elsevier, vol. 127(1), pages 1-12, September.
    8. Xiao, Tiaojun & Shi, Kuiran & Yang, Danqin, 2010. "Coordination of a supply chain with consumer return under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 124(1), pages 171-180, March.
    9. Li, Yongjian & Wei, Cansheng & Cai, Xiaoqiang, 2012. "Optimal pricing and order policies with B2B product returns for fashion products," International Journal of Production Economics, Elsevier, vol. 135(2), pages 637-646.
    10. Weaver, Robert D. & Moon, Yongma, 2011. "Pricing Perishables," 2011 International European Forum, February 14-18, 2011, Innsbruck-Igls, Austria 122007, International European Forum on Innovation and System Dynamics in Food Networks.
    11. Huang, Kwei-Long & Kuo, Chia-Wei & Lu, Ming-Lun, 2014. "Wholesale price rebate vs. capacity expansion: The optimal strategy for seasonal products in a supply chain," European Journal of Operational Research, Elsevier, vol. 234(1), pages 77-85.
    12. Mak, Vincent & Rapoport, Amnon & Gisches, Eyran J., 2012. "Competitive dynamic pricing with alternating offers: Theory and experiment," Games and Economic Behavior, Elsevier, vol. 75(1), pages 250-264.
    13. Khouja, Moutaz & Park, Sungjune & Zhou, Jing, 2013. "A free gift card alternative to price discounts in the newsvendor problem," Omega, Elsevier, vol. 41(4), pages 665-678.
    14. Liang, Xiaoying & Ma, Lijun & Xie, Lei & Yan, Houmin, 2014. "The informational aspect of the group-buying mechanism," European Journal of Operational Research, Elsevier, vol. 234(1), pages 331-340.
    15. Zhao, Li & Tian, Peng & Xiangyong Li, 2012. "Dynamic pricing in the presence of consumer inertia," Omega, Elsevier, vol. 40(2), pages 137-148, April.

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