Data

Antitrust and User Union in the Era of Digital Platforms and Big Data

By Lin William Cong (Cornell University) & Simon Mayer (University of Chicago)

Firms’ production function in the digital era entails customers’ network adoption and data contribution. We model platform competition with endogenous pricing, user heterogeneity, network effects, infrastructure investment, and data collection and sharing, thereby providing a unifying framework to evaluate data-related antitrust policies. Similar to and interacting with network effects, data feedback, while improving service quality, may concentrate market power. Platforms thus strategically underprice initially but subsequently overcharge users, and can “collude” through data sharing. Meanwhile, because users are dispersed, they do not internalize the impact of their actions (e.g., data contribution and sharing) on (i) future service or product quality which affects all users, (ii) concentration of market power, and (iii) platforms’ incentives to innovate and invest in data infrastructure. We show that data sharing proposals (e.g., open banking and data vendor) and user privacy protections (e.g., GDPR and CCPA) fail to address inefficiencies in data-driven platform competition. We propose user union as a radical but effective solution for antitrust and consumer protection: a representative governing body coordinates users’ contribution to the platforms and maximizes user surplus.

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