基于多Agent的服装可持续消费行为建模与仿真

Multi-agent-based modeling and simulation of sustainable clothing consumption behavior

“双碳”目标下,随着服装消费引起的气候变化和环境污染等生态问题日益严重,迫切需要重新思考和重塑服装消费模式,推动服装消费向质量型、低碳化转变,从而实现服装产业的绿色转型。文章运用多Agent建模方法,构建服装可持续消费行为仿真模型,采用Netlogo平台进行仿真实验,探求服装可持续消费行为的影响机理。结果表明,消费者可持续消费认知、产品可持续性和设施供应条件均显著促进可持续消费行为;但不同强度下,产品可持续性和设施供应条件的推动作用存在差异。基于此,从可持续消费认知和供应条件两方面提出了引导中国消费者服装可持续消费行为的建议和对策。

Under the goal of achieving carbon peak and carbon neutrality,ecological issues from clothing consumption are escalating,posing significant pressure on the natural environment and challenges to the sustainable development of the clothing industry.Sustainable development encompasses a complex chain spanning from production to consumer behavior,yet current government measures,policies,regulations,and industrial strategies predominantly focus on the production sector,with inadequate attention paid to the consumption sector.Notably,unsustainable consumption trends like overconsumption,comparative consumption,and abandonment are becoming increasingly prevalent in the clothing consumption process.Consequently,actively guiding consumers towards sustainable clothing consumption behaviors is paramount.Current research on sustainable clothing consumption behavior largely revolves around empirical investigations that use statistical methods to analyze influencing factors,consumption intentions,and behaviors.While these studies are significant in reflecting the static characteristics of consumer behavior at a particular moment,they struggle to capture the complex,dynamic trends and macro-emergent effects of such behavior.To address this gap,our research employs a multi-agent modeling approach to simulate the mechanisms impacting sustainable clothing consumption behavior.This approach allows us to capture the emergent behaviors arising from interactions between individual consumers and the interactions between individuals and their environmental contexts in real-world scenarios.Based on a literature review,the study first analyzed sustainable clothing consumption behavior and its influencing mechanisms.Subsequently,utilizing the agent-based modeling and simulation(ABMS)method,a multi-agent conceptual model was developed to encapsulate the driving factors of sustainable clothing consumption behavior.Within this model,consumer agents,clothing product agents,product facility supply agents,and supervision agents were designed and characterized.Additionally,considering the individual heterogeneity observed in real-world social groups,three variables,namely trust,conformity,and willingness to accept,were integrated into the traditional Deffuant model to enhance the interaction mechanism of sustainable consumption cognition.Furthermore,a BP neural network model was formulated to serve as the decision-making mechanism for sustainable clothing consumption behavior.Ultimately,a simulation system model for sustainable clothing consumption behavior was constructed,and the simulation experiments were conducted by utilizing the Netlogo platform to analyze and evaluate the dynamics of sustainable clothing consumption behavior.This study introduced ABMS into the realm of sustainable clothing consumption,utilizing an enhanced Deffuant model to simulate the emergent group characteristics and trends in consumer behavior resulting from interactions between individuals and various factors.Results show that consumers’sustainable consumption cognition significantly promotes the sustainable consumption behavior of clothing.The beneficial intervention of any variable in product sustainability and facility supply conditions will effectively improve consumers’sustainable clothing consumption behavior.Specifically,product sustainability has a strong driving effect under low intensity,and product facility supply conditions have a strong driving effect under medium and high intensity.In the case of different combinations of supply conditions,the improvement of product sustainability and product facility supply conditions to a medium level or above will greatly promote the sustainable consumption behavior of consumers.Based on this method,the dynamic evolution from individual micro-behaviors to macro-behaviors in sustainable clothing consumption is realized,making the proposed strategies and recommendations highly targeted and practical.Additionally,by employing interdisciplinary theories and methods,a comprehensive and systematic research framework is formed,further enhancing the depth and breadth of the study.Based on a multi-agent model,an in-depth simulation study of sustainable clothing consumption behavior was conducted,providing new perspectives and methods for understanding and promoting sustainable consumption.By constructing a complex simulation environment,the study simulated the decision-making process of consumers when faced with different sustainable consumption choices,revealing how various factors influence consumers’sustainable consumption tendencies.This study not only provides theoretical insights in the realm of sustainable clothing consumption but also offers robust support for practical applications,so as to contribute to the green transformation and sustainable development of the clothing industry.