Carbon quota allocation modeling framework in the automotive industry based on repeated game theory: A case study of ten Chinese automotive enterprises

Ning Wang, Kai Shang, Yan Duan and Dandan Qin

Energy, 2023, vol. 279, issue C

Abstract: Carbon quota management system is a long-term effective mechanism to promote the sustainable development of automotive industry. However, issues such as the total amount and allocation mechanism of carbon quotas hinder countries' implementation of carbon quota policies in the automotive industry. To address these issues, this study uses the GREET model and system dynamics model to predict carbon emissions in the automotive industry and sets the total carbon quota for China's automotive industry. Furthermore, based on the ZSG-DEA model and Gini coefficient model, this study applies repeated game theory to propose a carbon quota allocation modeling framework for the automotive industry. The results show that the proposed allocation modeling framework achieves a balance between equity and efficiency while taking into account the interests of both the government and enterprises, and achieves an equitable allocation of carbon quotas among 10 representative automotive enterprises. This study can provide reference for the design of carbon quota management system in the automobile industry.

Keywords: Life-cycle carbon emissions; Vehicle sales prediction; Carbon quota allocation; Repeated game theory (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:279:y:2023:i:c:s0360544223014871

DOI: 10.1016/j.energy.2023.128093

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