Abstract: An evolutionary game model between platforms and users is constructed from the perspective of conserving public resources and supporting market development. The model explores formation conditions and stability of different equilibrium points under the scenario where users have the freedom to switch platforms. Based on theoretical deduction, numerical simulations using Octave are conducted to analyze the factors influencing platform’s algorithmic discrimination pricing and determine the conditions required for an ideal state without such pricing. Additionally, this study aims to explore alternative measures, aside from regulation, that can help achieve this ideal state. The results indicate that avoiding big data-enabled price discrimination against existing customers does not necessarily rely on means such as real-time monitoring or fines; fostering multiple platforms and promoting platform competition may be a more direct and feasible approach.

Key words: big data-enabled price discrimination against existing customers, algorithmic pricing, price discrimination, evolutionary game, simulation