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Robust Pricing with Refunds

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  • Hinnosaar, Toomas
  • Kawai, Keiichi

Abstract

Before purchase, a buyer of an experience good learns about the product's fit using various information sources, including some of which the seller may be unaware of. The buyer, however, can conclusively learn the fit only after purchasing and trying out the product. We show that the seller can use a simple mechanism to best take advantage of the buyer's post-purchase learning to maximize his guaranteed-profit. We show that this mechanism combines a generous refund, which performs well when the buyer is relatively informed, with non-refundable random discounts, which work well when the buyer is relatively uninformed.

Suggested Citation

  • Hinnosaar, Toomas & Kawai, Keiichi, 2020. "Robust Pricing with Refunds," CEPR Discussion Papers 14615, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:14615
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    Cited by:

    1. Rodivilov, Alexander, 2021. "A note on robust procurement contracts," Economics Letters, Elsevier, vol. 201(C).
    2. Casner, Ben, 2020. "Seller curation in platforms," International Journal of Industrial Organization, Elsevier, vol. 72(C).
    3. Qianjun Lyu, 2022. "Optimal Refund Mechanism," ECONtribute Discussion Papers Series 214, University of Bonn and University of Cologne, Germany.
    4. Pham, Hien, "undated". "a reprendre_ WP annulé," TSE Working Papers 21-1263, Toulouse School of Economics (TSE).

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    More about this item

    Keywords

    Optimal pricing; Robustness; Return policies; Refunds; Monopoly; Information design; Mechanism design;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly

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