Decision-making dynamic evolution among groups regarding express packaging waste recycling under different reference dependence and information policy

The reveal of express packaging waste recycling behavior evolution trend is crucial to waste management. Current models are mostly based on the classic expected utility theory, without considering groups are susceptible to internal and external factors. To address this drawback, we construct an evolutionary game model of express packaging waste recycling behavior by considering information policy and reference dependence factors to explore groups' decision-making with different initial adoption rates. A system dynamics simulation model based on survey data is then built, and simulation experiments are also designed to reveal the impacts of key factors on the evolution path of recycling behavior. The results show that, without information policy, groups cyclically oscillate around the initial state. The stable trend depends on the information intensity, and the information effect is marginal diminishing. Groups with a lower initial adoption rate will evolve to an ideal stable strategy only when information intensity exceeds the threshold of ten. Reference points can change behavior strategies and are characterized by significant loss aversion. The benefits and costs affect groups' adoption or rejection behaviors. These findings can provide new ideas for related research and offer a reference for the government to formulate efficient waste management policies.

Automated summary

The reveal of the evolutionary trend in express packaging waste recycling behavior is crucial for waste management. Current models based on expected utility theory fail to consider the susceptibility of groups to internal and external factors. To address this issue, this study constructs an evolutionary game model that incorporates information policy and reference dependence factors to explore the decision-making of groups with varying initial adoption rates. Simulation experiments based on survey data demonstrate the impacts of key factors on the evolution path of recycling behavior.