电商平台“大数据杀熟”的法律问题研究

Research on the Legal Issues of “Big Data Price Discrimination” on E-Commerce Platforms

摘要: 当今互联网技术发展迅猛，电商平台依托大数据与算法技术，实现了对消费者的精准画像与个性化服务推送，极大地提升了用户体验与平台收益。然而，部分商家滥用信息技术，通过差异化的定价策略对用户进行价格歧视，侵害了消费者合法权益的同时，也扰乱了市场秩序。本文拟剖析“大数据杀熟”的基本内容，阐明其具有技术依赖性、目标指向性及行为隐蔽性的特点，进而从价格歧视说与算法歧视说两个维度探讨其法律属性。同时文章指出，“大数据杀熟”不仅违反了《消费者权益保护法》中关于消费者公平交易权的规定，还侵犯了消费者的个人信息权益。文章通过对比分析欧盟与美国在“大数据杀熟”法律规制方面的实践经验，提出了可能完善我国法律规制的路径，包括修正知情同意原则、提供去标识化处理的技术保障、提升算法透明度以及设立专门的个人信息保护机构，以期为保障消费者权益、规范电商平台经营行为提供支持。

Abstract: With the rapid development of Internet technology, e-commerce platforms have leveraged big data and algorithm technologies to create precise consumer profiles and deliver personalized services, greatly enhancing user experience and platform revenue. However, some merchants abuse information technology to implement differentiated pricing strategies, engaging in price discrimination against users, which infringes on consumers’ legal rights and disrupts market order. This paper aims to analyze the basic content of “big data price discrimination,” clarify its characteristics of technological dependence, targeted orientation, and behavioral concealment, and further explore its legal attributes from the perspectives of price discrimination and algorithmic discrimination. The paper also points out that “big data price discrimination” not only violates the provisions of the Consumer Rights Protection Law regarding consumers’ right to fair transactions but also infringes on consumers’ personal information rights. Through comparative analysis of the legal regulatory practices in the European Union and the United States regarding “big data price discrimination,” the paper proposes potential paths to improve China’s legal regulations, including revising the principle of informed consent, providing technical safeguards for de-identification, enhancing algorithm transparency, and establishing specialized personal information protection agencies, aiming to support the protection of consumer rights and regulate e-commerce platform operations.