Spatial and temporal evolution of green logistics efficiency in China and analysis of its motivation

Bin Chen, Fang Liu, Yina Gao and Chong Ye ()
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Bin Chen: Fujian Jiangxia University
Fang Liu: Fuzhou University
Yina Gao: Fujian Jiangxia University
Chong Ye: Fuzhou University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 2, No 1, 2743-2774

Abstract: Abstract The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth.

Keywords: Green logistics efficiency; Super-SBM; GML index model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-022-02833-2

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