Government subsidy-penalty strategy to promote low-carbon multimodal transportation using dynamic-static combination mechanism

Xinghua Hu (), Ruizi Cheng, Jiahao Zhao and Xiaochuan Zhou
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Xinghua Hu: Chongqing Jiaotong University
Ruizi Cheng: Chongqing Jiaotong University
Jiahao Zhao: Chongqing Jiaotong University
Xiaochuan Zhou: Ltd

Palgrave Communications, 2025, vol. 12, issue 1, 1-20

Abstract: Abstract Multimodal transportation has emerged as a viable solution to reduce energy consumption and carbon emissions, garnering widespread support from and being implemented by various governments. However, the lack of robust promotional policies and incentives has led to limited participation and suboptimal regulatory efficiency, posing challenges to the sustainable growth of low-carbon multimodal transportation. To address these issues, this study first constructs an evolutionary game model with government and multimodal transport operators (MTOs) as the game subjects and proposes three dynamic and static subsidy-penalty combination mechanisms to address the limitations of the static subsidy-penalty mechanism. Then, this study verifies the results of the game analysis through case simulation and analysis, conducts a sensitivity analysis on the main parameters, and finally obtains the following conclusions: (1) The static subsidy-penalty mechanism lacks an evolutionarily stable strategy (ESS) in the game model. (2) The introduction of dynamic subsidy-penalty mechanisms results in varying ESSs across different combinations. (3) An increase in the dynamic subsidy coefficient adversely affects governmental regulation, whereas a higher static penalty can positively influence the low-carbon commitment of MTOs. (4) Reducing the costs of proactive government regulation and increasing the carbon tax rate are essential steps. The conclusions of this study offer strategic guidance to governments for shaping the development of low-carbon multimodal transportation.

Date: 2025
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DOI: 10.1057/s41599-025-05087-1

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