Big Data Price Discrimination: The Choice of First-Mover Advantage

This paper explores the decision-making mechanisms behind big data price discrimination on E-commerce platforms. Specifically, we innovatively account for the heterogeneity of consumers and suppliers, using repeat purchase rates and the probability of detecting big data price discrimination to characterize consumers and differentiate suppliers by their bargaining power. Based on this, we developed a game-theoretic model of platform decision-making in big data price discrimination. Our research finds that, in an oligopolistic competitive environment, implementing big data price discrimination is a dominant strategic behavior for the platform. It sacrifices consumer welfare to provide platforms with a competitive advantage as first movers. Additionally, stronger bargaining power from suppliers helps mitigate consumer welfare losses. Furthermore, when considering consumer switching costs, our results indicate that even if platforms are caught engaging in big data price discrimination, high switching costs buffer the loss of profits for the platforms.