The impact of competitive intelligence services on online marketplaces
研究在线市场中竞争情报服务对大小卖家和平台的影响，发现需求噪声高时平台应同时向两卖家提供该服务，需求不确定性低时只向大卖家提供可带来三方共赢。
Recent innovations have driven a steady increase in online marketplace transactions. To remain competitive, numerous marketplace platforms and independent data providers offer Competitive Intelligence Services (CIS), enabling sellers to explore not only their market potential but also that of their competitors. In this article, we employ a two-period game-theoretic approach to competitive learning to analyze the impact of CIS on participants with varying market shares in an online marketplace. In the presence of noisy demand signals, the online platform benefits from offering CIS to both sellers. This is because high demand noise makes demand exploration difficult for each seller in the first period. Consequently, price competition under poor knowledge of the price-demand relationship in the second period leads to a lower payoff for each seller as well as the platform. However, as demand uncertainty decreases, the platform prefers to induce CIS subscription exclusively for the seller with the larger market share. This scenario leads to signal-jamming behavior between the sellers, which results in a win-win-win situation for both sellers and the platform provider. Finally, we consider various model extensions and discuss the managerial implications for the design and regulation of competitive intelligence services in online marketplaces.