Evolutionary game analysis of promoting the development of green logistics under government regulation

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Abstract

Due to the strong negative externalities of traditional logistics, the green logistics that developed from traditional logistics has the advantages of saving resources and protecting the environment. However, in the competitive market en-vironment, enterprises will not implement green logistics based on their own revenues and competitiveness and, instead, will choose the best choice from the actions of a series of internal and external factors. To explore the effect of various factors on the implementation of green logistics by enterprises, this study constructs a tripartite evolutionary game model of the governments, logistics enterprises, and users from the perspective of the participants in the process of logistics greening and analyzes the evolutionarily stable strategies of each participant under different situations. Netlogo software is used to simulate and analyze the initial willingness of the participants, the intensity of government subsidies and fines, and the probability that the enterprises’ speculative behaviors are founded on the system’s evolutionary paths and results. The results demonstrate that the initial willingness of the governments, logistics enterprises, and users to participate has different effects on the evolutionary results of the system. Government subsidy and fine measures significantly impact the strategic choices of enterprises and users. Compared with users, enterprises are more sensitive to government subsidies, and compared with fines, government subsidies have a greater impact on enterprises’ behavior choices. Moreover, the governments should strengthen the publicity of green logistics, formulate judgement standards and an evaluation system for green enterprise logistics, and restrain the speculative behaviors of enterprises.

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APA

Dong, Y., & Yang, T. (2022). Evolutionary game analysis of promoting the development of green logistics under government regulation. Journal of University of Science and Technology of China, 52(9). https://doi.org/10.52396/JUSTC-2022-0067

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