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The Operational Advantages of Threshold Discounting Offers

Author

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  • Simone Marinesi

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Karan Girotra

    (Technology and Operations Management, INSEAD, 77305 Fontainebleau, Cedex, France)

  • Serguei Netessine

    (Technology and Operations Management, INSEAD, Singapore 138676)

Abstract

We study threshold discounting, or the practice of offering a discounted-price service if at least a prespecified number of customers signal interest in it, as pioneered by Groupon. We model a capacity-constrained firm, a random-sized population of strategic customers, a desirable hot period, and a less desirable slow period. Compared to a more traditional approach (slow period discounting or closure), threshold discounting has two operational advantages. First, the contingent discount temporally balances demand when the market for the service is large, and reduces supply of the service (preserving higher margins) when the market is small, allowing the firm to respond to the service’s unobserved market potential. Second, activation of the threshold discount signals the market state and the consequent service availability to strategic customers, inducing them into self-selecting the consumption period to one that improves the firm’s capacity utilization. Yet, threshold discounting can be harmful in situations with chronically low demand. In contrast with past work on strategic customers, their presence is advantageous to firms in our context. A calibrated numerical study shows that threshold discounting improves firm profits over a traditional approach by as much as 33% (7% on average).

Suggested Citation

  • Simone Marinesi & Karan Girotra & Serguei Netessine, 2018. "The Operational Advantages of Threshold Discounting Offers," Management Science, INFORMS, vol. 64(6), pages 2690-2708, June.
  • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:6:p:2690-2708
    DOI: 10.287/mnsc.2017.2740
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    References listed on IDEAS

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    1. Gérard P. Cachon & Robert Swinney, 2009. "Purchasing, Pricing, and Quick Response in the Presence of Strategic Consumers," Management Science, INFORMS, vol. 55(3), pages 497-511, March.
    2. Yiangos Papanastasiou & Nicos Savva, 2017. "Dynamic Pricing in the Presence of Social Learning and Strategic Consumers," Management Science, INFORMS, vol. 63(4), pages 919-939, April.
    3. Qian Liu & Garrett J. van Ryzin, 2008. "Strategic Capacity Rationing to Induce Early Purchases," Management Science, INFORMS, vol. 54(6), pages 1115-1131, June.
    4. Yongmin Chen & Tianle Zhang, 2015. "Interpersonal Bundling," Management Science, INFORMS, vol. 61(6), pages 1456-1471, June.
    5. Xuanming Su, 2007. "Intertemporal Pricing with Strategic Customer Behavior," Management Science, INFORMS, vol. 53(5), pages 726-741, May.
    6. Senthil K. Veeraraghavan & Laurens G. Debo, 2011. "Herding in Queues with Waiting Costs: Rationality and Regret," Manufacturing & Service Operations Management, INFORMS, vol. 13(3), pages 329-346, July.
    7. Ming Hu & Mengze Shi & Jiahua Wu, 2013. "Simultaneous vs. Sequential Group-Buying Mechanisms," Management Science, INFORMS, vol. 59(12), pages 2805-2822, December.
    8. 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.
    9. Crew, Michael A & Fernando, Chitru S & Kleindorfer, Paul R, 1995. "The Theory of Peak-Load Pricing: A Survey," Journal of Regulatory Economics, Springer, vol. 8(3), pages 215-248, November.
    10. Gérard P. Cachon & Robert Swinney, 2011. "The Value of Fast Fashion: Quick Response, Enhanced Design, and Strategic Consumer Behavior," Management Science, INFORMS, vol. 57(4), pages 778-795, April.
    11. Necati Tereyagoglu & Senthil Veeraraghavan, 2012. "Selling to Conspicuous Consumers: Pricing, Production, and Sourcing Decisions," Management Science, INFORMS, vol. 58(12), pages 2168-2189, December.
    12. Krishnan S. Anand & Ravi Aron, 2003. "Group Buying on the Web: A Comparison of Price-Discovery Mechanisms," Management Science, INFORMS, vol. 49(11), pages 1546-1562, November.
    13. Xuanming Su & Fuqiang Zhang, 2008. "Strategic Customer Behavior, Commitment, and Supply Chain Performance," Management Science, INFORMS, vol. 54(10), pages 1759-1773, October.
    14. Xiaoqing Jing & Jinhong Xie, 2011. "Group Buying: A New Mechanism for Selling Through Social Interactions," Management Science, INFORMS, vol. 57(8), pages 1354-1372, August.
    15. Jun Li & Nelson Granados & Serguei Netessine, 2014. "Are Consumers Strategic? Structural Estimation from the Air-Travel Industry," Management Science, INFORMS, vol. 60(9), pages 2114-2137, September.
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