Regulation of Fair Competition in Online Marketing from the Perspective of Algorithmic Discrimination—Focusing on “Big Data Price Discrimination” and “Paid Placement”

在数字经济浪潮下，算法于网络营销中广泛应用，“大数据杀熟”与“竞价排名”等算法歧视问题却接踵而至，严重冲击公平竞争秩序，损害消费者权益。本研究融合法学与网络营销学理论方法，深入剖析算法歧视。从技术和法律层面解构其概念，揭示算法偏见和算法不平等的双重维度及不同规制逻辑。以“大数据杀熟”和“竞价排名”为典型场景，分析其法律属性、竞争危害。针对现行法律规制在概念边界、规范供给、司法实践方面的困境，构建涵盖事前预防、事中干预、事后救济的分层规制体系。研究旨在为算法歧视行为规制提供可行法律路径，推动数字经济领域公平竞争，同时展望未来在算法伦理法律化、跨学科研究及国际规则制定等方向的发展。In the wave of the digital economy, algorithms are widely used in online marketing. However, algorithmic discrimination issues such as “big data price discrimination” and “paid placement” have emerged one after another, severely impacting the fair competition order and harming consumers’ rights and interests. This study integrates the theoretical methods of law and online marketing to deeply analyze algorithmic discrimination. It deconstructs its concept from technical and legal perspectives, reveals the dual dimensions of algorithmic bias and algorithmic inequality and their different regulatory logics. Taking “big data price discrimination” and “paid placement” as typical scenarios, it analyzes their legal nature and competitive harms. In response to the dilemmas in the current legal regulation regarding concept boundaries, normative supply, and judicial practice, a hierarchical regulatory system covering ex-ante prevention, in-process intervention, and ex-post relief is constructed. The research aims to provide a feasible legal path for regulating algorithmic discrimination behaviors, promote fair competition in the digital economy, and simultaneously look ahead to future developments in the legalization of algorithmic ethics, interdisciplinary research, and international rule-making.