“Sherlocking” and Platform Information Policy
Prof. Arijit Mukherjee
Professor
Michigan State University
Platform-run marketplaces may exploit third-party sellers’ data to develop competing products, but potential for future competition can deter sellers’ entry. We explore how this trade-off affects the platform’s referral fee and its own entry decision. We first characterize the platform’s optimal referral fee under full commitment on entry decision and study its economic implications. We then analyze the extent to which the platform’s own information sharing policy substitutes for its commitment to entry. We characterize the platform’s optimal information policy and examine how it interacts with the platform’s fee structure. Our findings highlight the importance of considering the platform’s fee structure as a regulatory response in the policy debates on marketplace regulation.