【论文信息】

Sui R, Gao R, Li J. Optimal data pricing decisions of competitive two-sided platforms with heterogeneous data costs[J]. Industrial Management & Data Systems, 2025: 1-30.

DOI: https://doi.org/10.1108/IMDS-04-2025-0497

【作者信息】

第一作者：眭蓉华，博士，副教授，研究方向：平台运营、供应链管理；

第二作者/共同一作：高瑞泽，博士，北京雁栖湖应用数学研究院助理研究员，研究方向：金融科技、量化投资、商务智能分析、数据资产研究；

第三作者/通讯作者：李金璞，清华大学博士研究生，研究方向：数字经济、数据经济与宏观金融。

【基金支持】

国家自然科学基金(72473013, 72192802, 72342008)；教育部人文社科项目(23YJC630151)；中国博士后科学基金（2024M750254）；重庆市自然科学基金（CSTB2023NSCQ-MSX0903）；重庆市社会科学规划项目（2023NDQN29）；重庆工商大学高层次人才启动项目（2355044）。

【论文摘要】

Purpose—In the digital economy, two-sided platforms increasingly operate as data intermediaries, establishing vital revenue streams and competitive differentiation. This study aims to explore how competing two-sided platforms, acting as data intermediaries, strategically optimize their collection and pricing of user-generated data under cost heterogeneity and varying affiliation behaviors.

Design/methodology/approach—This study uses the Hotelling model to construct a multi-stage game framework, analyzing data collection and the related pricing decisions for competitive platforms. Through equilibrium analysis and practical validation, we reveal how duopolistic platforms strategically select full/partial data collection regimes while optimizing pricing, explicitly incorporating per-unit collection costs and cross-sided network effects.

Findings—A significant cost advantage prompts differentiated collection strategies, whereas smaller cost gaps favor consistent partial collection by both. Under partial collection, the cost-disadvantaged platform gains disproportionately from increased data intake, driving more aggressive price adjustments. Rising marginal value of data usage can lead platforms to lower price to expand their user base and leverage higher per-unit data utility for greater profitability. Consumer affiliation predominantly shifts optimal pricing, while provider affiliation significantly alters collection decision.

Originality/value—This study innovatively analyzes platform pricing from the perspective of data intermediation. Departing from the most existing literature focused on product/service intermediation, this research advances the understanding of platform pricing by examining data’s unique role as a strategic asset. Formalizing non-rivalrous traits and near-zero re-production costs, this study reveals platforms’strategic tradeoffs between differentiated/consistent data strategies, offering insights for leveraging data assets to enhance competitiveness and support sustainable platform growth.