The Evolution of Price Discrimination in E-Commerce Platform Trading: A Perspective of Platform Corporate Social Responsibility

Abstract

The widespread use of data in e-commerce has facilitated the implementation of different pricing strategies for platforms and merchants. However, the excessive use of algorithms for differential pricing has sparked discussions about fairness and price discrimination, disrupting the platform trading system. To address this challenge, we adopt an evolutionary game approach to analyze the evolutionary strategies of all parties from the perspective of platform CSR. It is based on a special type of e-commerce platform trading in which major merchants have data analytics capabilities. We construct an evolutionary game model considering reputation and punishment, explore the impact of different situations and factors on the system’s evolutionary stability strategy, and conduct its verification via simulation experiments. The results show that long-term reputation is the internal driving force for platforms to fulfill responsibilities. The joint punishment of collusion is the external binding force. Consumer complaints are key to restricting merchants’ integrity operation. Moreover, penalties imposed by e-commerce platforms can help eradicate price discrimination. This study provides a new perspective to solve price discrimination in the digital era. Measures based on reputation and punishment can guide platforms to fulfill other social responsibilities.