What Are the Key Factors Affecting AI Algorithmic Price Discrimination in China? Evidence From Complex Adaptive Systems Modelling

ABSTRACT Algorithmic price discrimination exhibits the features of a complex adaptive system. This study adopts multi‐agent modelling and simulation methods to investigate the phenomenon of artificial intelligence (AI)‐driven algorithmic price discrimination, explore its governance mechanisms and promote its ethical advancement. Based on an in‐depth analysis of 120 simulation cycles across six distinct scenarios, the results demonstrate that longer algorithm cycles have no statistically significant effect on the total number of platform operators engaging in AI‐enabled algorithmic price discrimination. Enhanced financing capabilities of platform operators significantly contribute to a substantial increase in the count of such operators. Stricter law enforcement efforts and a higher probability of collusion remarkably reduce the number of platform operators participating in this practice. A decrease in algorithm reserves leads to a marked decline in the number of platform operators actively implementing AI‐driven algorithmic price discrimination. Among these influencing factors, changes in algorithm reserves exert the most pronounced impact, while the financial capabilities of platform operators rank second as the next most significant factor.