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Optimal Refund Mechanism

Author

Listed:
  • Qianjun Lyu

    (Institute for Microeconomics, University of Bonn)

Abstract

This paper studies the optimal refund mechanism when an uninformed buyer can privately acquire information about his valuation over time. In principle, a refund mechanism can specify the odds that the seller requires the product returned while issuing a (partial) refund, which we call stochastic return. It guarantees the seller a strictly positive minimum revenue and facilitates intermediate buyer learning. In the benchmark model, stochastic return is sub-optimal. The optimal refund mechanism takes simple forms: the seller either deters learning via a well-designed non-refundable price or encourages full learning and escalates price discrimination via free return. This result is robust to both good news and bad news framework.

Suggested Citation

  • Qianjun Lyu, 2022. "Optimal Refund Mechanism," ECONtribute Discussion Papers Series 214, University of Bonn and University of Cologne, Germany.
    • Handle: RePEc:ajk:ajkdps:214
    as

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    File URL: https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_214_2022.pdf
    File Function: First version, 2022
    Download Restriction: no
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    References listed on IDEAS

    as
    1. Toomas Hinnosaar & Keiichi Kawai, 2020. "Robust pricing with refunds," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 1014-1036, December.
    2. Alessandro Bonatti, 2011. "Menu Pricing and Learning," American Economic Journal: Microeconomics, American Economic Association, vol. 3(3), pages 124-163, August.
    3. Shi, Xianwen, 2012. "Optimal auctions with information acquisition," Games and Economic Behavior, Elsevier, vol. 74(2), pages 666-686.
    4. Daniel Krähmer & Roland Strausz, 2015. "Optimal Sales Contracts with Withdrawal Rights," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(2), pages 762-790.
    5. Justin P. Johnson & David P. Myatt, 2006. "On the Simple Economics of Advertising, Marketing, and Product Design," American Economic Review, American Economic Association, vol. 96(3), pages 756-784, June.
    6. Steven A. Matthews & Nicola Persico, 2007. "Information Acquisition and Refunds for Returns," Carlo Alberto Notebooks 54, Collegio Carlo Alberto.
    7. Lang, Ruitian, 2019. "Try before you buy: A theory of dynamic information acquisition," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1057-1093.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Jonas von Wangenheim, 2022. "Optimal Information Design of Online Marketplaces with Return Rights," CRC TR 224 Discussion Paper Series crctr224_2022_352v2, University of Bonn and University of Mannheim, Germany, revised Apr 2024.

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    More about this item

    Keywords

    buyer learning; refund contract; information design; implementable mechanism;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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