Environmental efficiency and technological progress of transportation industry-based on large scale data

Hongwei Liu, Jie Wu and Junfei Chu

Technological Forecasting and Social Change, 2019, vol. 144, issue C, 475-482

Abstract: In order to measure technological change and environmental efficiency precisely, and further to improve the technology and environmental efficiency of road transportation industry in “big data” context, a Hicks-Moorsteen Index model based on DEA is proposed in this study, and then is employed to assess the performance of road transportation industry. The empirical study concludes that: (a) all of the total factors productivity growth, technological progress and environmental efficiency of the road transportation sectors in the eastern, western and central regions all averagely increased. (b) The growth rates of mix efficiency of the road transportation sectors in the three regions were the highest among the various efficiency changes. (c) While the performances of technological progress in western and central region outperform that in eastern region, the performance of environmental efficiency change outperform those in western and central regions. This paper suggests the diffused utilization of optimal production technology should be superior to the pace of technological innovation in western and central regions, and road transportation industry in China should be sensitive to the influence of government policy such as “supply side reform”.

Keywords: Road transportation; Technological progress; Environmental efficiency; TFP; Hicks-Moosteen index number (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162517314981
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:144:y:2019:i:c:p:475-482

DOI: 10.1016/j.techfore.2018.02.005

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().