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author:

Chen, Lei (Chen, Lei.) [1] | Wang, Ying-Ming (Wang, Ying-Ming.) [2] (Scholars:王应明)

Indexed by:

EI CSCD

Abstract:

It is of great significance to reasonably evaluate the environmental efficiency of the transportation industry, because it is related to the transportation industry' s sustainable development of green and low-carbon. Based on data envelopment analysis with undesirable outputs, the environmental efficiency of China' s regional transportation industry is evaluated; and combining with Meta-frontier Malmquist index analysis, the dynamic changes in its environmental efficiency during 2007-2016 is analyzed from the perspective of regional technical differences. The results show that the environmental efficiency of China's transportation industry is growing slowly on the whole, and there is still much room for improvement. Meanwhile, due to the influence of regional technological differences, the transportation industries in the eastern, central and western areas of China have different advantages and disadvantages in terms of environmental efficiency. On this basis, the corresponding policy suggestions are proposed in this paper to help all regions improve their environmental efficiency of transportation industry. Copyright © 2018 by Science Press.

Keyword:

Data envelopment analysis Efficiency Green manufacturing Sustainable development Systems engineering

Community:

  • [ 1 ] [Chen, Lei]School of Economics & Management, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Wang, Ying-Ming]School of Economics & Management, Fuzhou University, Fuzhou; 350116, China

Reprint 's Address:

  • 王应明

    [wang, ying-ming]school of economics & management, fuzhou university, fuzhou; 350116, china

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Source :

Journal of Transportation Systems Engineering and Information Technology

ISSN: 1009-6744

Year: 2018

Issue: 6

Volume: 18

Page: 22-27 and 54

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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