Plain language summary

With the increasing popularity of big data technology, some enterprises use the massive amount of consumer data collected for the analysis of consumers’ purchasing power and preferences to implement discriminatory pricing and increase profits, with consumer rights infringed upon. Therefore, it is of great significance to study how consumers respond to big data discriminatory pricing (BDDP) behavior by enterprises. This article categorizes consumers into new and old users. In the strategy sets of whether consumers choose to purchase and whether enterprises engage in discriminatory pricing, the costs and benefits of consumer rights protection and enterprise compensation are considered, respectively. A new “government-consumer-enterprise” tripartite game model is proposed, along with an analysis of different behavioral strategy combinations of the three parties. The impact of key parameters on each party is studied through simulation analysis to provide a reference for cracking down on BDDP behavior. The experimental results indicate that increasing government punishment and credibility can effectively suppress the BDDP behavior by enterprises; however, increasing the compensation limit for enterprises will only have a certain effect in the early stage; the higher the evaluation value of products or services by consumers, the less effectiveness it is in suppressing the BDDP behavior by enterprises.

Using game theory to simulate and analyze the best strategies of government, consumers, and enterprises under big data discriminatory pricing

Big data discriminatory pricing refers to enterprises setting different prices for different consumers based on the collected consumer information, which is a violation of consumer rights. Therefore, after reading relevant literature, this article adopts game theory methods to divide consumers into new and old users, constructs a tripartite game model of “government consumer enterprise,” calculates the profit matrix, replicates the dynamic equation, and Jacobian matrix of different strategies, Then, based on the eigenvalues, the stability and behavioral strategies of the three entities were analyzed. Through simulation analysis, the impact of several key parameters on the evolution and convergence of the game among each entity was studied, providing reference opinions for combating big data cheating behavior and safeguarding consumer rights.

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Simulation Analysis of Big Data Discriminatory Pricing Behavior from the Perspective of Game Theory

Designing for human rights in AI