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Privacy, Personalization, and Price Discrimination

Author

Listed:
  • Sinem Hidir

    (Princeton University)

  • Nikhil Vellodi

    (Princeton University, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

We study a bilateral trade setting in which a buyer has private valuations over a multi-product seller's inventory. We introduce the notion of an incentive-compatible market segmentation (IC-MS)—a market segmentation compatible with the buyer's incentives to voluntarily reveal their preferences. Our main result is a characterization of the buyer-optimal IC-MS. It is partially revealing, comprised primarily of pooling segments wide enough to keep prices low but narrow enough to ensure trade over relevant products. We use our results to study a novel design problem in which a retail platform seeks to attract consumers by calibrating the coarseness of its search interface. Our analysis speaks directly to consumer privacy and the debate regarding product steering versus price discrimination in online retail.

Suggested Citation

  • Sinem Hidir & Nikhil Vellodi, 2021. "Privacy, Personalization, and Price Discrimination," Post-Print halshs-02973614, HAL.
    • Handle: RePEc:hal:journl:halshs-02973614
    DOI: 10.1093/jeea/jvaa027
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    Cited by:

    1. Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
    2. Dirk Bergemann & Alessandro Bonatti, 2024. "Data, Competition, and Digital Platforms," American Economic Review, American Economic Association, vol. 114(8), pages 2553-2595, August.
    3. Mauring, Eeva, 2022. "Search and Price Discrimination Online," CEPR Discussion Papers 15729, C.E.P.R. Discussion Papers.
    4. Yassine Lefouili & Leonardo Madio & Ying Lei Toh, 2024. "Privacy Regulation and Quality‐Enhancing Innovation," Journal of Industrial Economics, Wiley Blackwell, vol. 72(2), pages 662-684, June.
    5. Skreta, Vasiliki & Doval, Laura, 2021. "Purchase history and product personalization," CEPR Discussion Papers 15969, C.E.P.R. Discussion Papers.
    6. Alireza Fallah & Michael I. Jordan & Ali Makhdoumi & Azarakhsh Malekian, 2024. "The Limits of Price Discrimination Under Privacy Constraints," Papers 2402.08223, arXiv.org, revised Jun 2024.
    7. Min Liu & Sajid Anwar, 2023. "Can price discrimination improve the performance of online retail platforms?," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 257-271, June.
    8. repec:hal:journl:hal-04774302 is not listed on IDEAS
    9. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    10. Liang, Annie & Madsen, Erik, 2024. "Data and incentives," Theoretical Economics, Econometric Society, vol. 19(1), January.
    11. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jul 2024.
    12. Amir Habibi, 2023. "Communicating Preferences to Improve Recommendations," Rationality and Competition Discussion Paper Series 394, CRC TRR 190 Rationality and Competition.
    13. Patel, Pankaj C. & Oghazi, Pejvak & Arunachalam, S., 2023. "Does consumer privacy act influence firm performance in the retail industry? Evidence from a US state-level law change," Journal of Business Research, Elsevier, vol. 162(C).
    14. Saara Hämäläinen & Vaiva Petrikaitė, 2024. "Prediction algorithms in matching platforms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(3), pages 979-1020, November.
    15. Vera Konrad & Andreas Polk, 2020. "Big Data und Preisdiskriminierung [Big Data and Price Discrimination]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 100(10), pages 793-798, October.

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