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Dynamic pricing when consumers are strategic: Analysis of posted and contingent pricing schemes

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  • Dasu, Sriram
  • Tong, Chunyang

Abstract

We study dynamic pricing policies for a monopolist selling perishable products over a finite time horizon to strategic buyers. Buyers are strategic in the sense that they anticipate the firm's price policies. It is expensive and administratively difficult for most brick and mortar retailers to change prices, placing limits on the number of price changes and the types of pricing policies they can adopt. The simplest policy is to commit to a set of price changes. A more complex alternative is to let the price depend on sales history. We investigate two pricing schemes that we call posted and contingent pricing. Using the posted pricing scheme, the firm announces a set of prices at the beginning of the horizon. In the contingent pricing scheme, price evolution depends upon demand realization. Our focus is on the posted pricing scheme because of its ease of implementation. Counter to intuition, we find that neither a posted pricing scheme nor a contingent pricing scheme is dominant and the difference in expected revenues of these two schemes is small. Limiting the number of price changes will result in a decrease in expected revenues. We show that a multi-unit auction with a reservation price provides an upper bound for expected revenues for both pricing schemes. Numerical examples suggest that a posted pricing scheme with two or three price changes is enough to achieve revenues that are close to the upper bound. Dynamic pricing is only useful when strategic buyers perceive scarcity. We study the impact of scarcity and derive the optimal stocking levels for large markets. Finally, we investigate whether or not it is optimal for the seller to conceal inventory or sales information from buyers. A firm benefits if it does not reveal the number of units it has available for sale at the beginning of the season, or subsequently withholds information about the number of units sold.

Suggested Citation

  • Dasu, Sriram & Tong, Chunyang, 2010. "Dynamic pricing when consumers are strategic: Analysis of posted and contingent pricing schemes," European Journal of Operational Research, Elsevier, vol. 204(3), pages 662-671, August.
  • Handle: RePEc:eee:ejores:v:204:y:2010:i:3:p:662-671
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    References listed on IDEAS

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    1. Milgrom,Paul, 2004. "Putting Auction Theory to Work," Cambridge Books, Cambridge University Press, number 9780521536721, December.
    2. Qian Liu & Garrett J. van Ryzin, 2008. "Strategic Capacity Rationing to Induce Early Purchases," Management Science, INFORMS, vol. 54(6), pages 1115-1131, June.
    3. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    4. Daniel Levy & Mark Bergen & Shantanu Dutta & Robert Venable, 1997. "The Magnitude of Menu Costs: Direct Evidence from Large U. S. Supermarket Chains," The Quarterly Journal of Economics, Oxford University Press, vol. 112(3), pages 791-824.
    5. K. Sridhar Moorthy, 1988. "Product and Price Competition in a Duopoly," Marketing Science, INFORMS, vol. 7(2), pages 141-168.
    6. Mark J. Zbaracki & Mark Ritson & Daniel Levy & Shantanu Dutta & Mark Bergen, 2004. "Managerial and Customer Costs of Price Adjustment: Direct Evidence from Industrial Markets," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 514-533, May.
    7. Xuanming Su, 2007. "Intertemporal Pricing with Strategic Customer Behavior," Management Science, INFORMS, vol. 53(5), pages 726-741, May.
    8. Harris, Milton & Raviv, Artur, 1981. "A Theory of Monopoly Pricing Schemes with Demand Uncertainty," American Economic Review, American Economic Association, vol. 71(3), pages 347-365, June.
    9. Krishna, Vijay, 2009. "Auction Theory," Elsevier Monographs, Elsevier, edition 2, number 9780123745071.
    10. Lazear, Edward P, 1986. "Retail Pricing and Clearance Sales," American Economic Review, American Economic Association, vol. 76(1), pages 14-32, March.
    11. Gabriel R. Bitran & Susana V. Mondschein, 1997. "Periodic Pricing of Seasonal Products in Retailing," Management Science, INFORMS, vol. 43(1), pages 64-79, January.
    12. 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.
    13. Constantinos Maglaras & Joern Meissner, 2006. "Dynamic Pricing Strategies for Multiproduct Revenue Management Problems," Manufacturing & Service Operations Management, INFORMS, pages 136-148.
    14. Netessine, Serguei, 2006. "Dynamic pricing of inventory/capacity with infrequent price changes," European Journal of Operational Research, Elsevier, vol. 174(1), pages 553-580, October.
    15. Coase, Ronald H, 1972. "Durability and Monopoly," Journal of Law and Economics, University of Chicago Press, vol. 15(1), pages 143-149, April.
    16. 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.
    17. David Besanko & Wayne L. Winston, 1990. "Optimal Price Skimming by a Monopolist Facing Rational Consumers," Management Science, INFORMS, vol. 36(5), pages 555-567, May.
    18. Yossi Aviv & Amit Pazgal, 2008. "Optimal Pricing of Seasonal Products in the Presence of Forward-Looking Consumers," Manufacturing & Service Operations Management, INFORMS, vol. 10(3), pages 339-359, December.
    19. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
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    Cited by:

    1. Liberali, Guilherme & Gruca, Thomas S. & Nique, Walter M., 2011. "The effects of sensitization and habituation in durable goods markets," European Journal of Operational Research, Elsevier, vol. 212(2), pages 398-410, July.
    2. 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.
    3. Qian Liu & Dan Zhang, 2013. "Dynamic Pricing Competition with Strategic Customers Under Vertical Product Differentiation," Management Science, INFORMS, vol. 59(1), pages 84-101, August.
    4. 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.
    5. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    6. repec:eee:phsmap:v:490:y:2018:i:c:p:70-76 is not listed on IDEAS
    7. Jiang, Yuanchun & Shang, Jennifer & Liu, Yezheng & May, Jerrold, 2015. "Redesigning promotion strategy for e-commerce competitiveness through pricing and recommendation," International Journal of Production Economics, Elsevier, vol. 167(C), pages 257-270.
    8. Yang, Daojian & Qi, Ershi & Li, Yajiao, 2015. "Quick response and supply chain structure with strategic consumers," Omega, Elsevier, vol. 52(C), pages 1-14.
    9. Ensthaler, Ludwig & Giebe, Thomas, 2014. "Bayesian optimal knapsack procurement," European Journal of Operational Research, Elsevier, vol. 234(3), pages 774-779.
    10. Rana, Rupal & Oliveira, Fernando S., 2014. "Real-time dynamic pricing in a non-stationary environment using model-free reinforcement learning," Omega, Elsevier, vol. 47(C), pages 116-126.
    11. Yu, Yugang & Liu, Jie & Han, Xiaoya & Chen, Can, 2017. "Optimal decisions for sellers considering valuation bias and strategic consumer reactions," European Journal of Operational Research, Elsevier, vol. 259(2), pages 599-613.

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