Spatial Association Network Structure and Influencing Factors of Carbon Emission Efficiency in China’s Logistics Sector

Authors

  • Lanlan Zhu
  • Ruiqi Zhu

DOI:

https://doi.org/10.62051/ijgem.v4n3.14

Keywords:

Carbon Emission Efficiency in Logistics, Spatial Correlation Networks, Influencing Factors, Social Network Analysis

Abstract

Based on relational data and a network perspective, this study calculates the carbon emission efficiency of China's logistics industry from 2006 to 2021 and analyzes the characteristics of the spatial correlation network structure of this efficiency through social network analysis. The results are as follows: (1) During the study period, the carbon emission efficiency of China's logistics industry exhibited a fluctuating downward trend, with notable regional disparities. Overall, there was an imbalance among regions, with the eastern region showing higher efficiency than the central region, and the central region higher than the western region. (2) From the perspective of the overall network structure, the spatial correlation of carbon emission efficiency in China's logistics industry tended to become closer, with a relatively stable and balanced spatial correlation structure. Additionally, (3) differences in spatial distance, economic development level, energy intensity, urbanization level, and industrial structure had significant impacts on the formation of the spatial correlation network of carbon emission efficiency in China's logistics industry.

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References

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Published

22-10-2024

Issue

Section

Arcicles