Paper
28 March 2023 The research of low carbon logistics efficiency and intelligent development based on data analysis
LiHong Han, GuiRong Li
Author Affiliations +
Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 1259728 (2023) https://doi.org/10.1117/12.2671848
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China
Abstract
The logistics sector plays a crucial role in promoting the implementation of the "carbon peak" policy and the high-quality improvement of China's economy as it is an industry with excessive energy consumption. In this study, the logistics efficiency of 30 Chinese provinces and cities (districts) is measured using the DEA model, and the factors influencing China's low-carbon logistics efficiency are identified using the Tobit regression model. The findings show that efficiency varies greatly between regions of China, with an east to west trending steady drop. The low comprehensive efficiency of logistics industry is mainly restricted by technical conditions. The efficiency of low-carbon logistics is positively impacted by per capita GDP, region entropy, and transport network density, but negatively impacted by R&D spending and energy intensity. This study puts forward some countermeasures and suggestions on the application of logistics public information service platform to narrow regional logistics differences, improve transport structure and develop smart logistics
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LiHong Han and GuiRong Li "The research of low carbon logistics efficiency and intelligent development based on data analysis", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 1259728 (28 March 2023); https://doi.org/10.1117/12.2671848
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KEYWORDS
Industry

Carbon

Carbon dioxide

Energy efficiency

Transportation

Analytical research

Reflection

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