报告题目 | Asymmetric Information of Product Authenticity on C2C E-Commerce Platforms: How Can Inspection Services Help? | |
报告人（单位） | 方心（新加坡管理大学李光前商学院） | |
主持人（单位） | 陈静（东南大学） | 李四杰（东南大学） |
时间地点 | 时间：2022年 8月 5日（周五） 上午 10点30分 腾讯会议ID：557-330-945 | |
报告内容摘要 | We consider product counterfeiting on a customer-to-customer platform that provides an inspection service. We develop a two-stage game-theoretical model. In the first stage, the platform designs a contract specifying commission and penalty fees. In the second stage, a seller signals his product authenticity by setting a price and a buyer decides whether to purchase it. This results in a contract design problem that governs a signaling game. We find that the effect of inspection is beyond merely detecting counterfeits. The inspection, even an imperfect one, changes the signaling game's structure and incentivizes the seller who likely has an authentic product to sell through the platform. This can only be achieved by carefully choosing the commission and penalty fees. Interestingly, a higher platform's expected profit does not imply a higher price or commission fee in equilibrium. Under some mild conditions, the optimal commission increases but the optimal penalty decreases as the platform’s inspection capability improves. | |
报告人简介：
Xin Fang is Associate Professor of Operations Management at Lee Kong Chian School of Business, Singapore Management University. He earned his Ph.D. in Operations Management from Carnegie Mellon University in 2014, and his B.S. in Information Systems from Fudan University in 2008. Xin studies the problems related to competition and coopetition in global supply chains and digital economy. His research applies cooperative and non-cooperative game theory as well as the theory of social and economic networks to the areas of decentralized distribution systems, corporate social responsibility and online platforms. His work has been published in journals such as Manufacturing & Service Operations Management, Operations Research and Production and Operations Management. | ||
