User-Generated Data Network Effects and Market Competition Dynamics

Hacohen, Uri Y.

Journal: Fordham Intellectual Property, Media and Entertainment Law Journal

Volume: 34

Year: 2023

Bluebook Citation: 34 FORDHAM INTELL. PROP. MEDIA & ENT. L.J. (2023)

Author: Uri Y. Hacohen: all 5 publications


Abstract

This Article defines User-Generated Data (“UGD”) network effects, distinguishes them from the more familiar concept of traditional network effects, and explores their implications for market competition dynamics. It explains that UGD network effects produce various efficiencies for digital service providers (“data platforms”) by empowering their services’ optimization, personalization, and continuous diversification. In light of these efficiencies, competition dynamics in UGD-driven markets tend to be unstable and lead to the formation of dominant multi-industry conglomerates. These processes will enhance social welfare because they are natural and efficient.

Conversely, countervailing UGD network effects also empower data platforms to detect and neutralize competitive threats, price discriminate among users, and manipulate users’ behaviors. The realization of these effects will result in inefficiencies, which will undermine social welfare. After a comprehensive analysis of conflicting economic forces, this Article sets the ground for informed policymaking. It suggests that emerging calls to aggravate antitrust enforcement and to “break up” Big Tech are ill-advised.

Instead, this Article calls for policymakers to draw inspiration from traditional network industries’ public utility and open-access regulations.

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