全球反壟斷監管科技發展現狀與趨勢

The Status Quo and Prospects of Science and Technology Development in Relation to Global Antitrust Regulation

數字技術伴生的商業模式演化，給反壟斷執法帶來挑戰的同時，也促進了全球反壟斷監管科技的發展。部分國家和國際組織近年加大反壟斷監管科技的調研力度，斯坦福大學的“計算反壟斷”項目更是吸引全球60多個國家、地區的反壟斷執法部門參與，體現了各國的高度重視。當前全球主要反壟斷轄區的監管科技應用，體現了融合計算科技的大趨勢。針對卡特爾的自動化檢測工具是當前各國最為重視的領域，經營者集中領域監管科技的適用尚處于起步階段，聚焦濫用市場支配地位方面的監管科技各國則鮮有涉及。影響當前各國反壟斷監管科技進一步發展的重要問題包括機構設計、數據支撑、技術局限以及公衆信任等方面。為提升我國反壟斷智慧監管水平，執法部門應深化理論研究、重視數據積累、側重特定行為，幷關注國際發展。

The evolution of business models, motivated by digital technologies, not only poses challenges to antitrust enforcement, but also promotes the development of science and technology (S&T) with respect to global antitrust regulation. In recent years, some countries and international organizations have intensified the research into antitrust regulatory S&T. Taking the Stanford University’s "Computational Antitrust" project as an example, it has attracted participation of antitrust enforcement agencies from over 60 countries and regions worldwide, reflecting the high attention paid by relevant stakeholders. The nowadays application of regulatory S&T by major antitrust jurisdictions around the world embodies the general trend of computational S&T integration. Antitrust enforcement agencies have paid most attention to automated detection tools to fight against cartels, which are followed by merger control, to which the application of regulatory S&T is in its infancy. Regulatory S&T against abuse of dominant market position has been rarely discussed about. Key issues obstructing the further development of antitrust regulatory S&T include institutional design, data support, technology limitation, and public trust, among others. To improve China’s intelligent antitrust regulation, law enforcement agencies should deepen theoretical research, value data accumulation, prioritize certain behaviors, and pay attention to international development.