Demand information sharing on retail platforms under seller information asymmetry
研究了零售平台在两类卖家（知情与不知情）信息不对称时，如何设计信息共享策略以优化市场效率和平台收益，发现平台应优先向不知情卖家独家共享信息。
Information asymmetry between informed and uninformed sellers poses a critical challenge for retail platforms, necessitating differentiated information-sharing strategies. This paper examines how a platform should design its information-sharing policy when serving two heterogeneous seller types (informed with private demand signals vs. uninformed) under Cournot competition. Our study bridges classic Cournot models with platform-centric information economics by introducing seller heterogeneity. By characterising equilibrium production decisions and Pareto-improving strategies, we provide actionable insights for platforms to optimise information services while enhancing market efficiency. We develop a game-theoretic model where sellers with asymmetric initial information engage in Cournot competition. The platform strategically shares demand signals through a noise-injection mechanism to maximise commission revenue, considering four sharing formats. Our analysis shows that the platform has incentives to share information exclusively with uninformed sellers, as this approach is most beneficial for the overall market. Furthermore, there exists a Pareto region in which informed sellers do not suffer from information leakage. Finally, we identify a pricing mechanism to maximise market efficiency. These findings provide valuable guidance for platform managers aiming to design effective information-sharing services that enhance both market efficiency and platform profitability. Specifically, the results suggest that platform managers should prioritise an exclusive information-sharing strategy targeted at uninformed sellers. Moreover, platforms can adopt differentiated pricing mechanisms to encourage participation from these sellers and thereby achieve optimal market performance.