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Data, Competition, and Digital Platforms

Author

Listed:
  • Dirk Bergemann
  • Alessandro Bonatti

Abstract

A monopolist platform uses data to match heterogeneous consumers with multiproduct sellers. The consumers can purchase the products on the platform or search off the platform. The platform sells targeted ads to sellers that recommend their products to consumers and reveals information to consumers about their match values. The revenue-optimal mechanism is a managed advertising campaign that matches products and preferences efficiently. In equilibrium, sellers offer higher qualities at lower unit prices on than off platform. The platform exploits its information advantage to increase its bargaining power vis-à-vis the sellers. Finally, privacy-respecting data-governance rules can lead to welfare gains for consumers.

Suggested Citation

  • Dirk Bergemann & Alessandro Bonatti, 2024. "Data, Competition, and Digital Platforms," American Economic Review, American Economic Association, vol. 114(8), pages 2553-2595, August.
    • Handle: RePEc:aea:aecrev:v:114:y:2024:i:8:p:2553-95
    DOI: 10.1257/aer.20230478
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    Citations

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    Cited by:

    1. Du, Weijian & Li, Mengjie, 2025. "Corporations’ digital attitude and digital technology innovation: Are the heart and mouth in agreement or not?," Finance Research Letters, Elsevier, vol. 75(C).
    2. Agur, Itai & Ari, Anil & Dell’Ariccia, Giovanni, 2025. "Bank competition and household privacy in a digital payment monopoly," Journal of Financial Economics, Elsevier, vol. 166(C).
    3. repec:nbr:nberch:14785 is not listed on IDEAS
    4. Kuerbis, Brenden & Mueller, Milton, 2023. "Exploring the role of data enclosure in the digital political economy," Telecommunications Policy, Elsevier, vol. 47(8).
    5. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, pages 73-96, National Bureau of Economic Research, Inc.
    6. Peneder, Michael & Bilek-Steindl, Sandra & Bärenthaler-Sieber, Susanne & Bock-Schappelwein, Julia & Charos, Alexandros, 2025. "Business use of online platforms: Competition, satisfaction and willingness to pay," Technology in Society, Elsevier, vol. 82(C).
    7. Bergemann, Dirk & Bonatti, Alessandro & Wu, Nick, 2023. "Managed Campaigns and Data-Augmented Auctions for Digital Advertising," CEPR Discussion Papers 18087, C.E.P.R. Discussion Papers.
    8. Teddy Mekonnen & Bobak Pakzad-Hurson, 2024. "Competition, Persuasion, and Search," Papers 2411.11183, arXiv.org, revised Sep 2025.
    9. Dirk Bergemann & Alessandro Bonatti & Nicholas Wu, 2025. "How Do Digital Advertising Auctions Impact Product Prices?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 92(4), pages 2330-2358.
    10. Carl-Christian Groh, & Jonas von Wangenheim, 2024. "Pigou Meets Wolinsky: Search, Price Discrimination, and Consumer Sophistication," CRC TR 224 Discussion Paper Series crctr224_2024_527, University of Bonn and University of Mannheim, Germany.
    11. 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.
    12. Liu, Ernest & Ma, Song & Veldkamp, Laura, 2025. "Data sales and data dilution," Journal of Financial Economics, Elsevier, vol. 169(C).
    13. Cristina Simone & Antonio Laudando, 2025. "Principles and obligations of the Digital Markets Act in regulating the economic power of gatekeepers: Positive, negative or trade-off effects?," Electronic Markets, Springer;IIM University of St. Gallen, vol. 35(1), pages 1-27, December.
    14. Du, Weijian & Cheng, Cheng & Li, Mengjie, 2025. "Can listed company digitization reduce the risk of export failure? Evidence from multisource heterogeneous data in China," International Review of Economics & Finance, Elsevier, vol. 103(C).
    15. Bergemann, Dirk & Bonatti, Alessandro & Wu, Nicholas, 2025. "Bidding with budgets: Data-driven bid algorithms in digital advertising," International Journal of Industrial Organization, Elsevier, vol. 102(C).

    More about this item

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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