Information Sharing on Retail Platforms

Problem definition : This paper studies the information-sharing strategy for a retail platform on which multiple competing sellers distribute their products. Academic/practical relevance : Because of the rapid growth of retail platforms in recent years, information sharing has become an increasingly important issue because retail platforms can gather an enormous amount of consumer information that may not be visible to the sellers. Understanding how to share such information with those sellers will provide useful implications from both the theoretical and practical perspectives. Methodology : We develop a game-theoretic model where multiple sellers engage in Cournot competition on a retail platform by selling substitutable products, and the platform charges a commission fee for each transaction. The platform owns superior demand information and can control the accuracy level when sharing the information with the sellers. Results : We find that the platform has incentives to share the information, and such sharing is beneficial both to the platform and to all sellers. Under the asymmetric information-sharing format, the optimal strategy for the platform is to select a subgroup of sellers and truthfully share information with them. Under the symmetric sharing format, the platform must use the same accuracy level and the same set of information for all sellers, and thus has incentives to reduce the accuracy of the shared information. Moreover, we identify a simple pricing mechanism that can achieve the optimal information-sharing outcome. Managerial implications : This research highlights the importance of considering the impact of information sharing for a retail platform with competing sellers. It also proposes a simple, single-price mechanism to implement the optimal sharing strategy. These results could provide useful guidelines for platform managers to better design their information-sharing services.