REVIEW ARTICLE
Measurement and Analysis of Logistics Energy Efficiency in China from Perspective of Total Factor Productivity
Zhang Li-Guo*, 1, 2
Article Information
Identifiers and Pagination:
Year: 2014Volume: 8
First Page: 624
Last Page: 629
Publisher Id: TOMEJ-8-624
DOI: 10.2174/1874155X01408010624
Article History:
Received Date: 12/11/2014Revision Received Date: 08/01/2015
Acceptance Date: 20/01/2015
Electronic publication date: 31/12/2014
Collection year: 2014
© 2014 Zhang Li-Guo
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Based on data envelopment analysis model (DEA), this paper constructs a measure function of logistics energy efficiency. Using provincial panel data from 2003 to 2009, it measures logistics energy efficiency in China from perspective of total factor productivity and analyzes the dynamic changes and regional disparity of logistics energy efficiency. The results show that, (1) the average growth rate of energy consume of China logistics is 13.8%, and the output value of that is only 5.7%;(2) The highest efficiency province is Hebei and the lowest is Yunnan which is only 0.3547. (3) The logistics energy efficiency of China in three regions was found while the East is best which 0.815 is, and the West is the worst which is 0.472.
Keywords: Data envelopment analysis model, energy efficiency, logistics industry.
