A Review of the Impact Pathways of Differential Pricing Driven by Big Data on Consumer Perceived Betrayal

In recent years, the phenomenon of price discrimination driven by big data has frequently emerged, causing considerable distress to consumers. This study, based on psychological reactance theory and fairness theory, employs a literature review method to explore the mechanism by which differential pricing driven by big data affects consumer perceived betrayal. It reveals the mediating effects of perceived unfairness and anger, as well as the moderating effect of psychological reactance. The results show that differential pricing positively affects consumer perceived betrayal, with perceived price unfairness and anger acting as mediators, and consumer psychological reactance traits serving as a moderator. This study elucidates the specific mechanisms and boundaries of the impact of differential pricing on consumer perceived betrayal, extending research on the psychological impact of differential pricing on consumers. This has practical implications for platform companies aiming to enhance consumer trust and provides a basis for regulating the use of platform algorithms.