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author:

Ye, C. (Ye, C..) [1] | Chen, N. (Chen, N..) [2] | Weng, S. (Weng, S..) [3] | Xu, Z. (Xu, Z..) [4]

Indexed by:

Scopus

Abstract:

The Belt and Road Initiative puts higher requirements for the logistics industry. As one of the most energy-consuming industries, logistics is a high-carbon emission industry. Its impact on the environment cannot be ignored. In this context, how to respond to the “Belt and Road” under the concept of sustainable development, to promote the logistics industry to achieve “low consumption, low emissions, high efficiency” of regional sustainability, has become the most important development of China’s logistics industry. Therefore, based on previous research, this paper establishes an input–output index system and uses the SBM-DEA model and Malmquist index model to analyze the efficiency of low-carbon logistics in 17 provinces from 2006 to 2020, explore the overall level of the logistics and the factors affecting efficiency, and compare the efficiency in different periods and regions. Then, through the Tobit regression model, the four main factors affecting the efficiency of the logistics industry are analyzed. The results show that: (1) The highest value of low-carbon logistics efficiency of each province is 1.0000, and the lowest value is only 0.0944. The difference in logistics efficiency values among provinces is large, so there is great room for improvement and development potential. (2) From 2006 to 2020, the low-carbon logistics efficiency of the regions showed an overall upward trend, and the MI index values of each province reached or approached the DEA effective state. Among them, technological progress has a promoting effect, while scale and pure technical efficiency have hindered the efficiency growth. (3) Economic growth and industry structure have a positive effect, while energy consumption and government expenditure are negatively correlated with efficiency. © 2022 by the authors.

Keyword:

Belt and Road carbon emissions logistics efficiency regional sustainability SBM model Tobit model

Community:

  • [ 1 ] [Ye, C.]School of Economics and Management, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Chen, N.]School of Economics and Management, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Weng, S.]School of Management, Xiamen University, Xiamen, 361005, China
  • [ 4 ] [Xu, Z.]School of Finance and Business, Shanghai Normal University, Shanghai, 200234, China

Reprint 's Address:

  • [Weng, S.]School of Management, China;;[Xu, Z.]School of Finance and Business, China

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Source :

Sustainability (Switzerland)

ISSN: 2071-1050

Year: 2022

Issue: 15

Volume: 14

2 . 5 9 2

JCR@2018

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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