Evolutionary Study Of Manufacturers’ Carbon Trading And Emission Reduction Decisions Based On Agent Based Modeling

As global climate change and environmental pollution become more severe,countries worldwide are increasingly embracing a common development direction of low-carbon economy and green development.Constructing low-carbon supply chains is crucial in promoting sustainable economic development,reducing energy consumption,and mitigating carbon emissions.It is a vital approach towards achieving a low-carbon economy and green development,leading to enhanced product quality and competitiveness,among other benefits.Carbon trading policy is one of the important means to promote the construction of low-carbon supply chains,which can provide necessary policy support and market mechanisms for enterprises,and promote enterprises to gradually transform towards a low-carbon economy.However,in practice,the impact of consumers’ purchasing needs on manufacturers’ carbon trading and emission reduction decisions is still a topic that requires further research.Therefore,this study aims to explore the relationship between consumers’ purchasing decisions and manufacturers’ carbon trading and emission reduction decisions,and based on this,a computational experimental model is constructed.The results of the study indicate that consumers’ individual attributes and network characteristics have a significant impact on manufacturers’ average carbon emissions,sales volume,carbon trading prices,and profits.Under the baseline rule,the increase in the intensity of consumer conformity tendencies leads manufacturers to reduce carbon emissions while maintaining relatively stable sales.Consumers’ preference for low carbon leads to a decrease in carbon emissions by manufacturers and a corresponding increase in profits for low carbon-emitting manufacturers.Under the grandfather rule,a moderate number of consumer neighbor nodes favor the sale of low carbon products,and over time,the sales of low carbon-emitting manufacturers surpass those of high carbon-emitting manufacturers.Furthermore,an increase in the probability of consumer reconnection enables low carbon-emitting manufacturers to achieve high sales and stable profits more quickly,while reducing the manufacturers’ average carbon emissions and maintaining higher carbon trading prices.Through the analysis of this study,we have explored the relationship between consumers’ purchasing decisions and manufacturers’ carbon trading and emission reduction decisions in depth,providing an important reference for the formulation of carbon trading policies.Moreover,this study has constructed an agent-based modeling,taking into account factors such as consumers’ individual attributes and network characteristics,which enhances the scientific and practicality of the research.In addition,the performance indicator evolutionary analysis method based on the grandfather rule and the baseline rule proposed in this study is helpful for manufacturers to comprehensively evaluate and optimize their carbon trading and emission reduction strategies,further improving the economic benefits and social responsibilities of enterprises and promoting sustainable development.Therefore,the results of this study have important theoretical and practical significance,and will have a positive promoting effect on research and practice in related fields.