Evolutionary Game Analysis of the Transformation from Traditional Logistics to Green Logistics under the Background of Dual Carbon
- DOI
- 10.2991/978-94-6463-262-0_75How to use a DOI?
- Keywords
- double carbon target; Green logistics; Reverse logistics; Evolutionary game
- Abstract
Green logistics is an important measure in response to national energy conservation and emission reduction policies, and in the long run, it is also a necessary measure to save costs for enterprises. This article aims to address the obstacles in the transition from traditional logistics to green logistics, and constructs a four party evolutionary game model of government, environmental NGOs, logistics enterprises, and consumers. The model consists of top-down transportation, bottom-up circulation, forward logistics, and reverse logistics to form a green logistics loop; Several Equant are solved by establishing duplicate dynamic equations, Jacobian matrix and determinant, etc., and the local stability of Equant is analyzed by using Lyapunov's first rule.By analyzing the evolutionary game model, this study explores the impact of government policies on corporate behavior, thereby providing reference for the formulation of relevant policies by government departments.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Mengfei Hou AU - Qinghong Xie PY - 2023 DA - 2023/10/09 TI - Evolutionary Game Analysis of the Transformation from Traditional Logistics to Green Logistics under the Background of Dual Carbon BT - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023) PB - Atlantis Press SP - 721 EP - 733 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-262-0_75 DO - 10.2991/978-94-6463-262-0_75 ID - Hou2023 ER -