基于 B2C 电子商务模式和生命周期评估框架的观光电动车供应链环境影响研究

Q2 Energy
Wei Xia, Chunjun Luo, Li Cai, Juan Yan, Xiaojiang Zhou, Yuan Zhang
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Environmental impact study of the sightseeing electric vehicle supply chain based on the B2C e-commerce model and LCA framework

Studying the impact of the electric vehicle supply chain on the environment is crucial for determining the future development direction of the industry. We have developed a method for evaluating the impact of supply chains on the environment based on a lifecycle framework. This method innovatively seeks the connection between the lifecycle process of physical products and the supply chain, and organizes the environmental impact assessment factors of the electric vehicle supply chain from three aspects: physical resources, power energy, and waste emissions, in order to construct an LCA fuzzy comprehensive evaluation model for the electric vehicle supply chain. For the first time, the research method of transforming qualitative analysis into quantitative data was introduced into the life cycle environmental impact assessment, and empirical research was conducted using the supply chain of sightseeing electric vehicles as an example. The results indicate that the scrapping stage of electric vehicles has the most severe impact on the environment. Strengthening research on strategies or technologies for handling waste batteries and automobiles is key to improving the environmental performance of the supply chain. This method breaks through the requirements and limitations of traditional life cycle assessment methods on data sources and parameters, avoids large-scale calculations that cannot be separated from subjective factors in traditional methods, simplifies the process of supply chain environmental impact assessment, shortens the evaluation time, and improves the efficiency of environmental impact assessment. It is more practical and has good application prospects.

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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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