A Three-Party Evolutionary Game Study Considering Green Travel under Government Regulation
Authors
Wenjie Zhang1, Haisheng Yu1, *
1School of Mathematics and Statistics, Ludong University, Yantai, 264001, China
*Corresponding author.
Email: bhaisenltn@163.com
Corresponding Author
Haisheng Yu
Available Online 26 December 2025.
- DOI
- 10.2991/978-94-6463-958-2_29How to use a DOI?
- Keywords
- Evolutionary game; green travel modes; government regulatory policies; green transition; sustainable development
- Abstract
This study constructs a three-party evolutionary game model to analyze the strategic interactions among the government, green enterprises, and non-green enterprises under the green travel mode. Based on replicator dynamics and numerical simulations, the results show that strategies converge to stable equilibria. Appropriate subsidies encourage green efforts and enhance regulatory willingness, excessive regulatory costs weaken enforcement, and higher fines curb non-green firms’ high pricing, collectively fostering green transformation and providing policy insights for sustainable development.
- Copyright
- © 2025 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 - Wenjie Zhang AU - Haisheng Yu PY - 2025 DA - 2025/12/26 TI - A Three-Party Evolutionary Game Study Considering Green Travel under Government Regulation BT - Proceedings of the 5th International Conference on Management Science and Software Engineering (ICMSSE 2025) PB - Atlantis Press SP - 257 EP - 269 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-958-2_29 DO - 10.2991/978-94-6463-958-2_29 ID - Zhang2025 ER -