“Sherlocking” and Platform Information Policy

Jay Pil Choi (), Kyungmin Kim () and Arijit Mukherjee ()
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Jay Pil Choi: Department of Economics, Michigan State University, East Lansing, Michigan 48824; and Yonsei University Graduate School, Seoul 03722, South Korea
Kyungmin Kim: Department of Economics, Emory University, Atlanta, Georgia 30322
Arijit Mukherjee: Department of Economics, Michigan State University, East Lansing, Michigan 48824

Management Science, 2025, vol. 71, issue 11, 9812-9830

Abstract: Platform-run marketplaces may exploit third-party sellers’ data to develop competing products, but the threat of future competition can deter sellers’ entry. We explore how this trade-off affects the platform’s entry on the marketplace and the referral fee it charges to the third-party sellers. We first characterize the platform’s optimal fee under different degrees of commitment on its own entry policy. We show that full commitment maximizes not only the platform’s payoff but also consumer surplus, as the associated fee induces maximal entry by the sellers. Next, we show how and when the platform’s policy on information sharing between its marketplace and product divisions can substitute for its commitment to entry. We characterize the platform’s optimal information policy and examine how it interacts with the platform’s fee structure. We show that an outright ban on information sharing between the platform’s divisions can reduce consumer welfare as it may lead to a higher referral fee that thwarts sellers’ entry. Our findings highlight the importance of considering the platform’s fee structure as a strategic response in the policy debates on marketplace regulation.

Keywords: platform marketplace; referral fee; entry; information design (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:71:y:2025:i:11:p:9812-9830

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