Data-Driven Mergers and Data Monetization

Abstract

This paper develops a theoretical model to study how data monetization influences digital innovation and competition in data-driven mergers. Data monetization generates additional revenue for digital firms but imposes privacy costs on consumers, and heterogeneity in these costs reshapes market segmentation and competition. The analysis shows that data monetization can weaken innovation incentives and reduce consumer surplus. In concentrated markets, it also softens competition, lowering consumer welfare. Comparing personalized and uniform pricing schemes, the paper identifies novel interactions between data monetization, pricing strategies, and welfare outcomes.