Reward or punishment? An evolutionary game model for improving ecological governance

To enhance ecological governance capabilities, the Chinese government has implemented a unique performance-based contracting model (PBCM). It stipulates the government's regulatory responsibilities and the requirements for the enterprise in preventing and controlling invasive species. However, enterprises frequently engage in speculation and fraud in practice. Motivated by this realistic situation, we propose four strategies for enhancing the governance capabilities by using the dynamic evolutionary game theory, including the static reward and static punishment strategy (Strategy I), the dynamic reward and static punishment strategy (Strategy II), the dynamic punishment and static reward strategy (Strategy III), and the dynamic reward and dynamic punishment strategy (Strategy IV). Our study reveals the strategic evolution paths of both the government and the enterprise under different incentive mechanisms. The test results illustrate that the system stability is highest under Strategy IV, followed by Strategy III. Conversely, the Strategy I, as well as the Strategy II, are unable to form any evolutionarily stable point. Our study also demonstrates that performance punishment exhibits a clear threshold effect. The system stability can be significantly varied only by strengthening performance punishment within a certain range. Increasing regulatory costs or performance rewards may lead to more speculative behavior by companies, thereby weakening the government's regulatory capacity.