With the proposal of China’s “carbon peak, carbon neutral” strategy, the increasing awareness of low carbon production among consumers, and the government’s introduction of carbon trading mechanism and low carbon consumption subsidy policies, enterprises are facing good opportunities for development. However, how the government can reasonably formulate low carbon policies and how enterprises can implement optimal low-carbon production decisions are still key issues in China’s low-carbon transition development. In this context, this paper is based on the carbon trading mechanism and carbon consumption subsidies. In this context, based on the carbon trading mechanism, this paper focuses on green production and green consumption, considers the impact of low-carbon consumer preferences and government subsidies on enterprises’ low-carbon production decisions, and uses the optimal theory to study the optimal pricing strategy and the optimal carbon reduction strategy. The study shows that the increase in carbon price has a positive effect on the increase in enterprise profit; the increase of carbon emission has a negative effect on the increase of enterprise profit and the high carbon price will intensify this effect. In addition, changing the intensity of government subsidies to consumers will lead to the change of enterprise carbon emission strategy. The study of this paper provides a certain reference for the government to reasonably formulate carbon trading prices and consumer low-carbon subsidies. In addition, considering consumer low-carbon preferences is also conducive to promoting green production practices of enterprises, thus promoting the realization of the carbon neutral strategy.

Innovation is a game process; in particular, the behavior among multiple agents in responsible innovation is susceptible to the influence of benefits, risks, responsibilities, and other factors, resulting in unstable collaborative relationships. Therefore, this paper constructs a tripartite evolutionary game model including the government, enterprises, and the public, combined with system dynamics modeling to simulate and analyze the tripartite behavior strategy and sensitivity to relevant exogenous variables. The study shows that the tripartite game eventually converges to a stable state of the government active supervision, enterprises making responsible innovation, and the public’s positive participation. The positive participation of the public drives rapidly the game to a steady state, while the behavioral strategies of enterprises are more susceptible to the behavior of the government. Supervision cost, penalty amount, and value compensation are the most critical factors influencing the change of the corresponding agents’ behavior strategy, and the final strategic stability of tripartite is affected by multiple exogenous variables.

Against the backdrop of the growing popularity of blockchain technology, this study investigates blockchain adoption strategies for the fresh food supply chain (FFSC) under a carbon cap-and-trade (CAT) policy. Taking a two-echelon supply chain consisting of a supplier and a retailer as an example, we designed four blockchain adoption modes based on the supplier’s strategy (adopt or not) and the retailer’s strategy (adopt or not). Combining influencing factors such as consumers’ low-carbon preference, consumers’ freshness preference, and carbon trading price (CTP), we established four game-theoretic models. Using backward induction, we derived the equilibrium strategies for the supplier and retailer under different modes and analyzed the impact of key factors on these equilibrium strategies. The analysis yielded four key findings: (1) BB mode (both adopt blockchain) is the optimal adoption strategy for both FFSC parties when carbon prices are high, and consumers exhibit strong dual preferences. It most effectively mitigates the negative price impact of rising carbon prices by synergistically enhancing emission reduction efforts and freshness preservation efforts, thereby increasing overall profits and achieving a Pareto improvement in the benefits for both parties. (2) Consumers’ low-carbon preference and freshness preference exhibit an interaction effect. These two preferences mutually reinforce each other’s incentive effect on FFSC efforts (emission reduction/freshness preservation). Blockchain’s information transparency makes these efforts more perceptible to consumers, forming a synergistic “emission reduction-freshness preservation” cycle that further drives sales and profit growth. (3) The adoption of blockchain by either the supplier or the retailer significantly lowers the cost threshold for the other party to adopt blockchain, thereby increasing their willingness to adopt. (4) CAT and consumer preferences jointly influence the adoption strategies of suppliers and retailers. Additionally, the adoption strategies of FFSC participants are also affected by the other party’s blockchain adoption status. Drawing on the above conclusions, this study provides actionable guidance for suppliers and retailers in selecting optimal blockchain adoption strategies.

In this study, an innovative many-to-one two-sided matching decision method for complex decision problems in the matching of supply and demand of elderly care services is proposed. Faced with the challenges of diversified demand and uneven supply of elderly care services in the context of an aging population, existing matching methods have significant shortcomings in subjective preference expression, objective evaluation integration, and consideration of time factors. Therefore, a many-to-one matching model in picture fuzzy environment to achieve the best matching scheme between the elderly and pension institutions is constructed in this study. By using the minimum variance method and cumulative prospect theory, subjective preference satisfaction and objective matching results for the elderly and pension institutions are obtained, respectively. Combined with regret theory, the two are compared to obtain adjusted satisfaction, and an innovative time satisfaction index based on expected check-in time is proposed to construct a three-objective optimization model that includes virtual subjects. The research in this paper expresses the subjective evaluation of two-sided subjects in the form of picture fuzzy preference relation, which enriches the research of picture fuzzy theory. At the same time, the quality of pension service matching is further improved considering time satisfaction and objective matching results in the pension service model.