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Endorsements and Referrals: Product Recommendations in Bilateral Trade

Author

Listed:
  • Peter Achim
  • Bojia Li
  • Lily Ling Yang

Abstract

This paper examines how a monopoly seller strategically employs pricing strategies and incentive mechanisms to influence consumer learning in the presence of a third-party information provider. Without direct payments, the seller influences consumer learning indirectly through distinct pricing strategies, which either deter or induce information acquisition. With direct payments, the seller can influence recommendations directly. "Endorsements", which tie payments to recommendations, remove informativeness and unambiguously harm the buyer. In contrast, "referrals", which tie payments to sales, can enhance consumer surplus and can even lead to Pareto improvements.

Suggested Citation

  • Peter Achim & Bojia Li & Lily Ling Yang, 2025. "Endorsements and Referrals: Product Recommendations in Bilateral Trade," CRC TR 224 Discussion Paper Series crctr224_2025_657, University of Bonn and University of Mannheim, Germany.
  • Handle: RePEc:bon:boncrc:crctr224_2025_657
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    File URL: https://www.crctr224.de/research/discussion-papers/archive/dp657
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    References listed on IDEAS

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    1. Lewis, Tracy R & Sappington, David E M, 1994. "Supplying Information to Facilitate Price Discrimination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(2), pages 309-327, May.
    2. Daniele Condorelli & Andrea Galeotti & Vasiliki Skreta, 2018. "Selling through referrals," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(4), pages 669-685, October.
    3. Bester, Helmut & Ritzberger, Klaus, 2001. "Strategic pricing, signalling, and costly information acquisition," International Journal of Industrial Organization, Elsevier, vol. 19(9), pages 1347-1361, November.
    4. Anne-Katrin Roesler & Balázs Szentes, 2017. "Buyer-Optimal Learning and Monopoly Pricing," American Economic Review, American Economic Association, vol. 107(7), pages 2072-2080, July.
    5. Roman Inderst & Marco Ottaviani, 2009. "Misselling through Agents," American Economic Review, American Economic Association, vol. 99(3), pages 883-908, June.
    6. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    7. Admati, Anat R. & Pfleiderer, Paul, 1986. "A monopolistic market for information," Journal of Economic Theory, Elsevier, vol. 39(2), pages 400-438, August.
    8. Steven Salop & Joseph Stiglitz, 1977. "Bargains and Ripoffs: A Model of Monopolistically Competitive Price Dispersion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 44(3), pages 493-510.
    9. Martin, Daniel, 2017. "Strategic pricing with rational inattention to quality," Games and Economic Behavior, Elsevier, vol. 104(C), pages 131-145.
    10. Mark Armstrong & Jidong Zhou, 2011. "Paying for Prominence," Economic Journal, Royal Economic Society, vol. 121(556), pages 368-395, November.
    11. Tat-How Teh & Julian Wright, 2022. "Intermediation and Steering: Competition in Prices and Commissions," American Economic Journal: Microeconomics, American Economic Association, vol. 14(2), pages 281-321, May.
    12. Roman Inderst & Marco Ottaviani, 2012. "Competition through Commissions and Kickbacks," American Economic Review, American Economic Association, vol. 102(2), pages 780-809, April.
    13. Andrei Hagiu & Bruno Jullien, 2011. "Why do intermediaries divert search?," RAND Journal of Economics, RAND Corporation, vol. 42(2), pages 337-362, June.
    14. Tamer Boyac? & Yalçın Akçay, 2018. "Pricing When Customers Have Limited Attention," Management Science, INFORMS, vol. 67(7), pages 2995-3014, July.
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    More about this item

    Keywords

    Consumer learning; Monopoly pricing; Third-party information provision;
    All these keywords.

    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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