Mathematical modeling and numerical analysis of blockchain decision systems by a dynamic game method

In this study, we innovatively applied dynamic game theory to analyze blockchain adoption decisions in competitive environments. By constructing a multi-stage dynamic game model and solving for optimal strategies through backward induction, we overcame the limitations of the traditional static game analysis. Combining the mathematical modeling with numerical simulations, we identified a critical threshold effect of the competition intensity on the blockchain adoption equilibrium. Specifically, when the competition intensity fell below the threshold, blockchain adoptions emerged as the dominant strategy. Beyond this threshold, the equilibrium shifted to a mixed-strategy outcome. Furthermore, we developed a dynamic response mechanism that linked traceability preferences to profit functions. Our model provides a theoretical framework for analyzing blockchain adoptions in competitive settings, while the numerical results offer actionable insights for optimizing the blockchain system design.