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Evolutionary game analysis of big data discriminatory pricing diffusion based on the supervision of relevant interest parties

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  • JiWen Chai
  • LiHao Wang

Abstract

The use of big data technology is significant for the market competition of two‐side enterprises. However, big data technology is likely to become a tool for discriminatory pricing, causing damage to the benefit‐relevant parties. This paper constructs a four party evolutionary game model between two‐side enterprises, governments, suppliers, and consumers. Lotka–Volterra model is introduced to explore the evolutionary impact of the supervisory behaviors of the benefit‐relevant parties on the diffusion of big data discriminatory pricing (BDDP) in two‐side enterprises. Using MATLAB simulation tools, the evolution game and diffusion evolution model are mathematically deduced, and the analogue simulation is used for correlation analysis. This paper can help two‐side enterprises, governments, suppliers, and consumers better understand the diffusion law of BDDP and more accurately predict the development of it. At the same time, it provides a quantitative theoretical basis for the reasonable decision‐making of governments, suppliers, and consumers.

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  • JiWen Chai & LiHao Wang, 2023. "Evolutionary game analysis of big data discriminatory pricing diffusion based on the supervision of relevant interest parties," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2094-2101, June.
    • Handle: RePEc:wly:mgtdec:v:44:y:2023:i:4:p:2094-2101
    DOI: 10.1002/mde.3803
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