Self-Preferencing and Coordinated Conduct by Oligopolistic Platforms under Data Monopoly: Challenges and Antitrust Regulatory Responses

Abstract

In the era of the digital economy, data monopoly has emerged as a central factor reshaping the landscape of market competition. Leveraging exclusive access to data resources and algorithmic control, oligopolistic platforms systematically consolidate their dominant market positions through coordinated self-preferencing conduct, undermining fair competition and threatening consumer welfare. By analyzing the characteristics of data exclusivity, algorithmic coordination, cross-platform ecosystem foreclosure, and the quasi-public nature of platform power, this study reveals the dual harms to competition posed by data monopolies. Existing antitrust frameworks face significant institutional challenges, including outdated criteria for identifying market dominance, difficulties in proving tacit collusion via algorithms, and the lack of mechanisms for evaluating cross-market effects. To address these issues, this paper proposes a three-dimensional regulatory path encompassing technology, institutional reform, and law enforcement. Key recommendations include establishing a dedicated chapter on the abuse of digital platforms, reforming the criteria for assessing market dominance, optimizing the burden of proof allocation, and localizing the EU’s "digital gatekeeper" regime. These measures aim to strike a balance between innovation incentives and competitive fairness, offering a tailored regulatory framework for antitrust governance in China's digital economy.