Environmental issues recently have emerged as an important research problem. The enterprise’s green production and the government’s supervision is the keyway to reduce environmental hazards. Against this background, in this paper, we described green production supervision as a game between the enterprise and the government. Unlike previous studies, we considered the impact of limited resources of the enterprise when building the game model, which makes the model more in line with the actual situation. Because of the bounded rationality of the players, an evolutionary game model is built. The enterprise’s goal was profit maximization in the game. And the government’s goal was assumed to be social profit maximization. Solving the evolutionary game model, the evolutionarily stable strategy (ESS) of the model is obtained. Then, an impact analysis of how supervisory parameters affected the ESS is provided. Subsequently, we proposed some effective measures to reduce environmental hazards, such as increasing the penalty on the enterprise once pollution is discovered, reducing the mandatory green production cost reasonably, increasing the taxation ratio and improving public participation. The specific conditions of these parameters for better ESS are given based on the impact analysis. These conditions can guide the government’s decision-making in green production supervision.

Network environments have recently emerged as a considerable research area. In addition to government supervision, platform supervision is also critical to improve network environments. So, we should improve the social network platform’s single regulatory model. Against this background, we described public opinion supervision as a game between marketing accounts, netizens, and the platform. Unlike previous studies, we considered the influence of marketing accounts on online public opinion. Because of the players’ bounded rationality, we built an evolutionary game model, and by solving it, we obtained the evolutionarily stable strategy (ESS). Then, we analyzed the influence of relevant parameters on the evolutionary stable state. Our research results show that if the authenticity of the information is not high, to not publish is the best choice for the marketing account, and to not participate is the best choice for the netizen. The platform penalty for the marketing account is also directly related to the marketing account’s decision making. The platform penalty for the government, as well as the increase in the penalty risk coefficient, considerably affected the choice of platform. Finally, we put forward the “pre-event–in-the-event–post-event” three-stage supervision model, which provides countermeasures and suggestions for all parties to jointly maintain the network environment.

The entry of JD.com into the food delivery sector and the ensuing subsidy competition have resulted in irrational competition, merchant profit squeezes, and food safety risks in China. This study therefore investigates the collaborative governance mechanisms for food delivery platforms under involutionary competition driven by traffic contestation. A two-agent evolutionary game model between platforms and merchants is developed, and Q-learning simulations are conducted to capture dynamic learning behaviors. The analysis examines the effects of coupon face value, cost-sharing mechanisms, traffic incentives, and government incentive-penalty policies on the strategic choices of both agents. Key findings reveal that merchants are more sensitive than platforms to traffic incentives and government penalties. Traffic-dependent merchants and traffic-independent merchants exhibit significantly different responses to government interventions. The coupon face value demonstrates a threshold effect, where only a reasonable range encourages compliant behavior among both parties. Based on these results, a collaborative governance framework is proposed. For traffic-dependent merchants, the government should focus on regulating platform behaviors and supervising coupon value controls, while platforms should establish a reward-oriented, penalty-supported incentive mechanism. For traffic-independent merchants, the government should strengthen consumer-reporting penalty mechanisms and strictly control collusion risks between platforms and merchants. Platforms should increase inspection frequency and reinforce penalties to prevent, at the source, the decline in product quality and market disorder induced by involutionary competition. This study provides strategic insights for achieving collaborative governance of involutionary competition in platform economies under intense traffic contestation.