Analysis of the dynamic evolution of green technology innovation decision-making in the supply chain

Green technology innovation (GTI) breaks the vicious cycle of "economic development-environmental pollution," mitigating the supply chain carbon emissions. Previous research focused on exploring supply chain GTI decision-making in the discrete strategy space and ignored the effect of stochastic factors. This paper, grounded in the classical evolutionary game theory, explores the interaction mechanism of supply chain GTI decision-making between suppliers and manufacturers under stochastic interferences and in the continuous strategy space. The main findings are as follows. First, regardless of the game scenario, the government subsidy, carbon price, and consumer green preference are incentive variables, while the innovation cost coefficient is an inhibitory variable. As the incentive variables increase or the inhibitory variables decrease, the game system evolves from the negative to the intermediate state, ultimately converging to the ideal state. Second, the ideal state becomes unstable after considering stochastic interferences, reflecting the fragility of bilateral innovation alliances between suppliers and manufacturers. Simultaneously, the evolution of the game system towards the negative state is also hindered, and the corresponding variable condition region narrows. In other words, stochastic interferences have a dual impact on supply chain GTI strategies. Third, an absolute negative state of no innovation does not exist in the continuous strategy space. Suppliers and manufacturers can determine the optimal innovation intensity to maximize expected returns, making GTI decision-making more flexible and resilient. This paper enriches the theoretical achievements of the evolutionary game theory and provides a reference for GTI strategies of supply chain enterprises.