电商平台算法个性化定价的挑战与协同治理研究

Challenges and Collaborative Governance Study of Algorithmic Personalized Pricing on E-Commerce Platforms

摘要: 算法个性化定价俗称“大数据杀熟”，是电商平台数字化实践的核心体现，它依托算法模型深度挖掘用户数据以实现收益最大化，但同时也对平台经济的公平性基底与消费者信任构成了显著威胁。在电商平台的具体运营中，该行为游走于动态定价、用户画像歧视与自动化决策之间，导致平台在合规责任认定上陷入困境。本文认为，电商平台作为主要责任主体，应依据《中华人民共和国个人信息保护法》第24条关于自动化决策中“不合理的差别待遇”之规定，构建平台内外部协同的治理框架。研究首先剖析该定价模式对电商平台公示价格体系的冲击及对消费公平体验的侵蚀；进而揭示平台在履行算法解释义务、保障用户选择权以及应对合规监管时面临的实际难题。最终，本文从平台治理视角，提出电商平台算法个性化定价的协同治理路径：通过细化商业场景下的合理性判断标准、设计用户导向的权利实现机制；引入算法影响评估与审计以强化平台内控体系；优化基于平台交易特征的举证规则；并推动构建植根于平台内部的算法伦理。本研究旨在为数字经济时代电商平台的可持续运营与可信算法生态的构建提供治理学上的参考。

Abstract: Algorithmic personalized pricing, commonly known as “Big Data Price Discrimination”, is a core manifestation of digital practices in e-commerce platforms. It relies on algorithmic models to deeply mine user data to maximize revenue, yet it also poses a significant threat to the foundational fairness of the platform economy and consumer trust. In the specific operations of e-commerce platforms, this practice navigates between dynamic pricing, user profile discrimination, and automated decision-making, leading to difficulties in determining compliance accountability for platforms. This paper argues that e-commerce platforms, as the primary accountable entities, should establish an internally and externally collaborative governance framework based on the provision regarding “unreasonable differential treatment” in automated decision-making under Article 24 of the Personal Information Protection Law. The study first analyzes the impact of this pricing model on the transparent pricing systems of e-commerce platforms and its erosion of fair consumer experiences. It then reveals the practical challenges platforms face in fulfilling algorithmic explanation obligations, safeguarding user choice rights, and responding to compliance oversight. Finally, from the perspective of platform governance, this paper proposes a collaborative governance pathway for algorithmic personalized pricing on e-commerce platforms: by refining reasonableness judgment standards in commercial contexts and designing user-oriented rights realization mechanisms; introducing algorithmic impact assessments and audits to strengthen internal control systems; optimizing burden-of-proof rules based on platform transaction characteristics; and promoting the construction of algorithm ethics rooted within platforms. This study aims to provide governance insights for the sustainable operation of e-commerce platforms and the construction of a trustworthy algorithmic ecosystem in the era of the digital economy.