Insider Imitation
研究了平台利用第三方卖家数据推出自营产品如何抑制创新，以及数据使用限制如何重塑创新激励，为数字市场竞争政策提供参考。
We study how regulating data usage impacts innovation in digital markets. Platforms commonly use proprietary data about third-party sellers to inform their own competing offerings, dampening incentives for innovation. We model this interaction and characterize how data usage restrictions reshape these incentives. An outright ban on data usage may boost or curtail innovation, depending on the thickness of the right tail of demand for new products. More flexible rules controlling when and what data are made available can always improve the effectiveness of regulation. Our results contribute to an ongoing policy discussion regarding competition in digital markets.