Decision-making of Green Tourism Supply Chain Considering Risk Aversion under Government Subsidy
- DOI
- 10.2991/978-94-6463-262-0_38How to use a DOI?
- Keywords
- Green tourism supply chain; Stackelberg game theory; Government subsidy; Risk aversion
- Abstract
Based on Stackelberg game theory, a game model among the government, scenic spot and travel agency is established to address issues in the green tourism supply chain considering government subsidy and risk aversion. Equilibrium solutions for models under different circumstances are analyzed and compared, with numerical experiments conducted using MATLAB. The results of the study indicate that government subsidy have the power to mobilize enthusiasm within the scenic spot and further drive its development towards greener practices. Meanwhile, moderate government subsidies are advantageous in enhancing social welfare, but subsidy intensity must be cautiously controlled to avoid over-stimulation. Additionally, the enhancement of tourists' environmental awareness and the moderate increase in subsidy proportion both contribute to improving the greenness level of the scenic spot, bringing greater profits to the supply chain. Furthermore, the importance of risk aversion is evident in the decision-making process of supply chain management for the green tourism.
- 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 - Yi Zhang PY - 2023 DA - 2023/10/09 TI - Decision-making of Green Tourism Supply Chain Considering Risk Aversion under Government Subsidy BT - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023) PB - Atlantis Press SP - 341 EP - 352 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-262-0_38 DO - 10.2991/978-94-6463-262-0_38 ID - Zhang2023 ER -