Analysis of tripartite evolutionary game for maritime supply chain collaboration considering carbon emission governance

The maritime supply chain is undergoing a significant transformation as the industry converges on a consensus to promote low-carbon and sustainable development. In response, governments and international organizations have implemented and updated policies to establish greenhouse gas (GHG) emission targets for the shipping industry. Achieving green and low-carbon sustainable development in the maritime supply chain necessitates coordinated decision-making among three primary entities: governments, shipping companies, and port enterprises. In this paper, a combination of system dynamics (SD) and evolutionary game theory is employed to examine the decision-making behaviors of these three parties and analyze their evolutionary pathways. Data on recent investments by typical enterprises and government subsidies have been collected, and an SD model is utilized to empirically verify the overall evolutionary process of the system and conduct a sensitivity analysis. Our findings indicate that the intensity and stability of government regulatory policies are pivotal in driving the low-carbon transformation of the maritime supply chain. Notably, a nonlinear relationship is observed between the severity of government policies and enterprise decisions. Furthermore, the level of collaboration between port and shipping enterprises in selecting technological pathways directly impacts the effectiveness of emission reductions. Additionally, the extent of low-carbon preference in market demand significantly influences the effectiveness of policies and the strategic choices made by enterprises.

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Publication Details

Journal
Frontiers in Marine Science
Published
2025-03-04
DOI
https://doi.org/10.3389/fmars.2025.1552544
Citations
4
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
8.43
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article

Analysis of tripartite evolutionary game for maritime supply chain collaboration considering carbon emission governance

Ran Zhou, Xiaojun Li, Lin Zheng, Lequn Zhu
4 citations
Frontiers in Marine Science
Innovation Diffusion and Forecasting
8.43
article

Analysis of tripartite evolutionary game for maritime supply chain collaboration considering carbon emission governance

Ran Zhou, Xiaojun Li, Lin Zheng, Lequn Zhu
article en
4 citations

Abstract

The maritime supply chain is undergoing a significant transformation as the industry converges on a consensus to promote low-carbon and sustainable development. In response, governments and international organizations have implemented and updated policies to establish greenhouse gas (GHG) emission targets for the shipping industry. Achieving green and low-carbon sustainable development in the maritime supply chain necessitates coordinated decision-making among three primary entities: governments, shipping companies, and port enterprises. In this paper, a combination of system dynamics (SD) and evolutionary game theory is employed to examine the decision-making behaviors of these three parties and analyze their evolutionary pathways. Data on recent investments by typical enterprises and government subsidies have been collected, and an SD model is utilized to empirically verify the overall evolutionary process of the system and conduct a sensitivity analysis. Our findings indicate that the intensity and stability of government regulatory policies are pivotal in driving the low-carbon transformation of the maritime supply chain. Notably, a nonlinear relationship is observed between the severity of government policies and enterprise decisions. Furthermore, the level of collaboration between port and shipping enterprises in selecting technological pathways directly impacts the effectiveness of emission reductions. Additionally, the extent of low-carbon preference in market demand significantly influences the effectiveness of policies and the strategic choices made by enterprises.

Frontiers in Marine ScienceVol. 12
Tianjin Research Institute of Water Transport Engineering (CN)
Openalex Percentile: Top 3%
Innovation Diffusion and Forecasting
8.43
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