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Information Acquisition and Refunds for Returns

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  • Steven A. Matthews

    (Department of Economics, University of Pennsylvania)

  • Nicola Persico

    (Department of Economics and School of Law, New York University)

Abstract

A product exhibits personal fit uncertainty when its consumers have idiosyncratic and uncertain values for it. Often a consumer can learn her long-run value quickly by obtaining the good for a trial period. Money back guarantees of satisfaction are commonly used to lower the cost to consumers of learning their values this way. Increasingly, however, consumers can instead learn about their values before they purchase by, e.g., reading product reviews or consulting experts. We study the effect on a firm’s optimal price and refund of this competing source of information. An efficient outcome would be achieved by setting the refund for a return equal to its salvage value. But a monopoly will, for some parameters, induce consumers to stay uninformed by promising a refund that is greater than the salvage value. This generates an inefficiently large number of returns, which the firm finds worthwhile in order to eliminate the information rents that consumers would obtain by becoming informed. This finding is consistent with the observation that for many products, money back guarantees are generous, as they commonly refund the entire, or almost the entire, purchase price of a product.

Suggested Citation

  • Steven A. Matthews & Nicola Persico, 2007. "Information Acquisition and Refunds for Returns," PIER Working Paper Archive 07-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Handle: RePEc:pen:papers:07-021
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    References listed on IDEAS

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    2. Hoffmann, Florian & Inderst, Roman & Turlo, Sergey, 2018. "Regulating Cancellation Rights with Consumer Experimentation," EconStor Preprints 253659, ZBW - Leibniz Information Centre for Economics.
    3. Roman Inderst & Marco Ottaviani, 2013. "Sales Talk, Cancellation Terms and the Role of Consumer Protection," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(3), pages 1002-1026.
    4. Inderst, Roman & Tirosh, Gilad, 2011. "Refunds as a Metering Device," MPRA Paper 53846, University Library of Munich, Germany.
    5. Qianjun Lyu, 2024. "Optimal Refund Mechanism with Consumer Learning," Papers 2404.14927, arXiv.org.
    6. Qianjun Lyu, 2022. "Optimal Refund Mechanism," ECONtribute Discussion Papers Series 214, University of Bonn and University of Cologne, Germany.
    7. Bird, Davina & Garrod, Luke & Wilson, Chris M, 2024. "Consumer protection versus competition: the case of mandatory refunds," MPRA Paper 122125, University Library of Munich, Germany.
    8. Mandal, Prasenjit & Basu, Preetam & Saha, Kushal, 2021. "Forays into omnichannel: An online retailer’s strategies for managing product returns," European Journal of Operational Research, Elsevier, vol. 292(2), pages 633-651.
    9. Lee, Chang Hwan & Rhee, Byong-Duk, 2021. "Retailer-run resale market and supply chain coordination," International Journal of Production Economics, Elsevier, vol. 235(C).
    10. Jena, Sarat Kumar & Meena, Purushottam, 2022. "Shopping in the omnichannel supply chain under price competition and product return," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    11. Schumacher, Heiner, 2014. "Incentives through consumer learning about tastes," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 170-177.
    12. Lin, Jiaxin & Zhang, Juliang & Cheng, T.C.E., 2020. "Optimal pricing and return policy and the value of freight insurance for a retailer facing heterogeneous consumers with uncertain product values," International Journal of Production Economics, Elsevier, vol. 229(C).
    13. Inderst, Roman & Peitz, Martin, 2012. "Informing consumers about their own preferences," International Journal of Industrial Organization, Elsevier, vol. 30(5), pages 417-428.
    14. Sven Hoeppner, 2014. "The unintended consequence of doorstep consumer protection: surprise, reciprocation, and consistency," European Journal of Law and Economics, Springer, vol. 38(2), pages 247-276, October.
    15. Lee, Chang Hwan & Rhee, Byong-Duk, 2018. "Retailer-run resale market and optimal returns and resale policy," European Journal of Operational Research, Elsevier, vol. 268(2), pages 504-514.
    16. Inderst, Roman & Peitz, Martin, 2008. "Selling Service Plans to Differentially Informed Customers," ZEW Discussion Papers 08-125, ZEW - Leibniz Centre for European Economic Research.
    17. Jeffrey D. Shulman & Anne T. Coughlan & R. Canan Savaskan, 2009. "Optimal Restocking Fees and Information Provision in an Integrated Demand-Supply Model of Product Returns," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 577-594, December.

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    More about this item

    Keywords

    information acquisition; refunds; money back guarantees; personal fit uncertainty;
    All these keywords.

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

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