M&A and Innovation of Digital Platform Enterprises: The Role of Data Elements

【Authors】

ZHANG Guijuan, LIU Yubin, HUANG Junhong & XU Honghai

【WorkUnit】

【Abstract】

With intensifying market competition and the rapid advancement of digital technology, the strategic use of data resources to drive innovation, enhance enterprise competitiveness, and promote economic growth has been widely discussed. Platform enterprises, through Mergers and Acquisitions （M&A）, can quickly acquire data assets, enabling precision matching, personalized advertising, and improved service quality. The resultant profit growth provides vital funding for innovation. However, frequent M&A by platform companies may also lead to excessive data concentration, increased market power, weakened market competition, and the risk of monopolistic inertia, which may ultimately stifle innovation. From a data-driven perspective, it is imperative to examine how platform M&A shapes innovation and how different M&A strategies yield distinct effects on innovation. Addressing these questions not only helps platform enterprises make informed strategic decisions to enhance their competitive advantages but also equips regulators with the insights to effectively oversee platform M&A, data consolidation, and related activities.
This study develops a Salop model incorporating two-sided markets theory and data elements to theoretically analyze the impact and underlying mechanisms of data-driven M&A on platform innovation. Additionally, it employs a Propensity Score Matching （PSM） Difference-in-Differences （DID） econometric model, applied year by year, to empirically test our hypotheses using M&A transaction data and patent data from publicly listed digital platform companies between 2009 and 2021. The findings reveal that data-driven M&A has significantly enhanced the innovation performance of platform enterprises, with market power acting as a primary channel. However, excessive market power may eventually undermine innovation. Further heterogeneity analysis suggests that China’s emerging economy exhibits weaker innovation advantages from platform M&A compared to developed economies. Additionally, transaction platforms demonstrate stronger innovation momentum than non-transaction platforms. Moreover, intra-industry M&A and cross-border M&A spur greater innovation than inter-industry or domestic M&A.
The policy implications of this study are threefold. First, digital platform enterprises should adopt data-driven M&A strategies tailored to their specific contexts, to harness data as a driver of innovation and productivity. Second, antitrust authorities must remain vigilant against the risk of innovation stagnation caused by data-driven M&A and incorporate data assets into their market structure and competition assessments during M&A reviews. Third, domestic digital platform enterprises should be encouraged to expand globally to enhance their innovation capabilities and international competitiveness.
Grounded in two-sided markets theory, this study advances the understanding of data-driven platform M&A by constructing a mathematical model incorporating data elements and conducting empirical tests using data from platform enterprises. It enriches both the theoretical framework and empirical evidence on platform M&A and enterprise innovation. However, data limitations—particularly the lack of data on non-listed target platforms—limit our analysis to acquiring platforms. Future research should further explore the broader impact of large-scale digital platform M&A on target platforms, market dynamics, consumer welfare, and social well-being to inform public policy and regulatory frameworks.

【KeyWords】

Digital Platform, Mergers and Acquisitions, Innovation, Data Elements, Market Power