关键词: 公众参与, 政府行为, 绿色技术创新, Moran过程, 随机演化博弈

Abstract: Green technology, as an emerging environmental protection technology, promotes sustainable development by reducing carbon emissions and environmental pollution, serving as a key element for enterprises to optimize their energy structure, reduce carbon emissions, and enhance competitiveness, and becoming a new engine for high-quality development in China. In reality, on the one hand, decision-making for green technology innovation involves multiple stakeholders with characteristics of multi-subject relationships. The analysis of these relationships can provide a more specific and accurate framework for studying the driving forces of enterprise green technology innovation behavior; on the other hand, green technology innovation, with its characteristics of large investment, high risk, low short-term returns, and dual externalities, exhibits strong uncertainty in its returns. It is noteworthy that, at the present stage, decision-making for enterprise green technology innovation faces a more turbulent internal and external environment, bringing a high degree of uncertainty to the environment for enterprise green innovation.
Existing literature has extensively discussed the selection of green innovation strategies under multiple subjects using deterministic game models. The evolutionary game theory with determinism is based on bounded rationality, allowing game participants to continuously experiment and learn, and making it more realistic than the traditional game theory. In conclusion, this paper, based on the Moran process, starts from reality. In a context where a finite number of pollution enterprises face highly uncertain random factors, it considers the long-term evolutionary characteristics of pollution enterprises’ green technology innovation behavior, incorporates the interaction between the government and public in green innovation, constructs a stochastic evolutionary model for pollution enterprises’ green technology innovation decision-making, and analyzes, solves, and simulates the impact mechanisms of relevant important variables on the evolutionary dynamics of pollution enterprises’ green technology innovation decisions under different selection intensities. The results show that: (1)When the number of enterprises in the market is small, the driving conditions for green technology innovation strategies are the same under strong and weak selection. However, when the number of enterprises in the market is large, the riving conditions for green technology innovation strategies are more stringent under strong selection. (2)Under weak selection, the effects of different types of incentives on the selection of green technology innovation strategies vary with different numbers of enterprises: first, when the number of pollution enterprises exceeds a certain level, positive incentives are more likely to influence the selection of green technology innovation strategies compared to negative incentives, and vice versa when the number of pollution enterprises is below a certain level; second, regardless of the number of enterprises, public participation is more likely to have a positive effect on the selection of green technology innovation strategies compared to government actions, but when the number of pollution enterprises is below a certain level, public participation has a greater impact on the selection of green technology innovation strategies. Furthermore, this paper provides policy suggestions for promoting green technology innovation in the market with different numbers of enterprises.
Future research could further incorporate the impact of government market incentives on green technology innovation. Additionally, the influence of digitization and green finance on the strategy selection of pollution enterprises could be considered.

Key words: public participation, government behavior, green technology innovation, the Moran process, stochastic evolutionary game