市场支配地位、用户规模差异与平台个性化定价研究

王夕琛　曲创

（山东大学经济学院）

　　内容提要：本文在构建非对称平台竞争模型的基础上，引入平台间用户规模差异，对平台个性化定价进行分析。研究结果表明，小平台会跟随大平台的定价方式，而大平台会优先选择个性化定价；大平台通过个性化定价可以实现市场扩张并巩固其市场支配地位。在市场存在有效竞争的条件下，当大小平台都实施个性化定价时，消费者福利高于统一定价时的水平，且在两者势均力敌时达到最优；当引入数据可携权以促进用户数据在平台间流动时，将提升平台个性化定价下的消费者福利。因此，数字经济时代应审慎监管平台个性化定价行为，综合权衡短期与长期福利目标，根据市场竞争状况、用户规模、平台级别等因素进行个案分析和综合评估，营造公平有序的平台经济竞争环境。

　　　　　　　　

　　关键词：平台反垄断；平台分级；用户规模；个性化定价；数据可携权；消费者福利

　　　　　　　　

　　作者简介：王夕琛，山东大学经济学院博士研究生，济南，250100；曲创，山东大学经济学院教授、博士生导师。

　　　　　　　　

　　基金项目：国家社会科学基金青年项目“数字经济驱动制造业高质量发展的内在机理及实现路径研究”（20CJY026）；河南省高等学校重点项目“新时期河南省制造业发展质量测度与提升路径研究”（20A790028）

　　　　　　　　

　　引用格式：王夕琛,曲创.市场支配地位、用户规模差异与平台个性化定价研究[J].经济与管理研究,2023,44(4):39-55.DOI:10.13502/j.cnki.issn1000-7636.2023.04.003.

　　　　　　　　

Research on Market Dominance, User Scale Difference and Personalized Pricing

WANG Xichen, QU Chuang

(Shandong University, Jinan 250100)

　　　　　　　　

　　Abstract: In the digital economy, discriminatory pricing based on big data frequently occurs on platforms, causing widespread controversy and concerns about monopoly. With the development of big data, cloud computing and other technologies, the ability of platforms to collect consumer data and analyze consumer preferences continues to improve. Although large firms with market dominance implement price discrimination, many small platforms also engage in this behavior in the internet industry. Therefore, the paper investigates the impact of personalized pricing on market competition and consumer welfare, and examines whether the platform scale affects its pricing decision.

　　Based on the Hotelling model, this paper examines the pricing game of platforms considering differences in user scale. It also analyses the market equilibrium and the consequences of personalized pricing for dominant platforms by comparing different pricing combinations. The findings show that the choice of pricing strategy for the small platform depends on the large platform’s decision. The large platform prefers personalized pricing, which attracts more users and strengthens its market dominance. When there is effective competition in the market, consumer welfare will be higher than the uniform pricing level. When two platforms with equal strength engage in personalized pricing, consumer welfare reaches optimal. Moreover, consumer welfare under personalized pricing will be improved if the right to data portability is introduced to promote the transfer of user data between platforms.

　　Compared to existing studies, the marginal contribution of this paper is reflected in the following aspects. First, it examines the personalized pricing behavior of platforms from the perspective of platform grading. Second, the residual extraction effect and the competitive reinforcement effect are integrated into a unified analytical framework to analyze their impact on consumer welfare. Third, direct network externalities based on historical transaction volumes and user evaluations are incorporated into the analytical framework, making the theoretical analysis more practical. Fourth, the impact of data portability on the consequences of personalized pricing on platforms is introduced, providing a richer theoretical basis for platform regulation and antitrust enforcement.

　　Based on these findings, this paper provides the following policy insights. First, it should carefully supervise the personalized pricing behavior of platforms, with a comprehensive trade-off between short-term and long-term welfare objectives. Second, market structure, platform categorization, and network externalities should be considered when analyzing personalized pricing. Third, introducing the right to data portability can prevent harm to consumer welfare. Fourth, regulators should focus on large platforms with dominant positions, as the choices of the large platform can influence the pricing practices of small platforms.

　　Keywords: platform antitrust; platform grading; user scale; personalized pricing; right to data portability; consumer welfare