报告题目：Data or Insights? Platform Data Cooperation with Manufacturers for Product Improvement
报告人：孙灿
报告时间：2026年9月21日（周一）上午10:00-11:20
报告地点：明哲楼517
主办单位：东北财经大学现代供应链管理研究院
【报告人简介】
孙灿，男，中国科学技术大学特任研究员。2018年获加拿大阿尔伯塔大学商学院博士。主要研究方向为信息系统经济学、运营与信息系统交叉、信息技术对供应链与商业模式影响。主要研究成果发表在Information Systems Research，Production and Operations Management等期刊。主持国家自然科学基金面上、青年项目，参与国家自然科学基金重点项目。担任SSCI期刊Information Technology and Management的副编辑和Production and Operations Management的编辑审稿委员会成员。
【报告摘要】
Online platforms accumulate massive amounts of consumer data that can be leveraged to support manufacturers’ product improvement. This paper examines how a platform should engage in data cooperation with two competing manufacturers through either data sharing or insight sharing. We develop a game-theoretic model in which the platform chooses whether to share data or insights mined from data, while manufacturers decide whether to adopt the shared data or insights for product improvement. We show that the platform engages in data cooperation only when the product improvement cost is sufficiently low. Conditional on cooperation, the platform prefers data sharing when the data mining cost and consumer privacy cost are low; otherwise, it prefers insight sharing. Insight sharing always induces symmetric adoption and does not harm manufacturers. In contrast, data sharing may lead to asymmetric adoption; when competition is weak and the privacy cost is moderate, it can generate a prisoner’s dilemma in which both manufacturers adopt the shared data but are worse off than under no sharing. Data sharing induces greater product improvement than insight sharing only when the commission fee is low, the data mining cost is high, and the privacy cost is low. In terms of welfare, both sharing modes increase consumer surplus relative to no sharing in equilibrium. Insight sharing always increases social welfare, whereas data sharing may reduce it when the privacy cost is sufficiently high. Moreover, as data mining technology advances, an equilibrium shift from insight sharing to data sharing can reduce both consumer surplus and social welfare. These findings suggest that policymakers should promote privacy-preserving technologies that reduce privacy costs and expand the conditions under which data cooperation benefits platforms, manufacturers, and consumers simultaneously.
