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Data, Competition, and Digital Platforms

Dirk Bergemann and Alessandro Bonatti

No 2343R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: We analyze digital markets where a monopolist platform uses data to match multiproduct sellers with heterogeneous consumers who can purchase both on and off the platform. The platform sells targeted ads to sellers that recommend their products to consumers and reveals information to consumers about their values. The revenueoptimal 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 the platform. Privacy-respecting data-governance rules such as organic search results or federated learning can lead to welfare gains for consumers.

Keywords: Data; Data; Privacy; Data Governance; Digital Advertising; Competition; Digital Platforms; Digital Intermediaries; Personal Data; Matching; Price Discrimination; Automated Bidding; Algorithmic Bidding; Managed Advertising Campaigns; Showrooming (search for similar items in EconPapers)
JEL-codes: D18 D44 D82 D83 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2023-04
New Economics Papers: this item is included in nep-big, nep-com, nep-des, nep-gth, nep-ind, nep-mic, nep-pay and nep-reg
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https://cowles.yale.edu/sites/default/files/2023-04/d2343r.pdf (application/pdf)

Related works:
Journal Article: Data, Competition, and Digital Platforms (2024) Downloads
Working Paper: Data, Competition, and Digital Platforms (2023) Downloads
Working Paper: Data, Competition, and Digital Platforms (2022) Downloads
Working Paper: Data, Competition, and Digital Platforms (2022) Downloads
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