Wei Wang

Dr. Wei Wang

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2017 in Energy Policy
Verified
Journal Article
Closed access
HXHualin Xie
Hualin Xie
YYYanni Yu
Yanni Yu
WWWei Wang
Wei Wang
YLYanchu Liu
Yanchu Liu

1 November 2016 in Technological Forecasting and Social Change
Verified
Journal Article
Closed access
HXHualin Xie
Hualin Xie
WWWei Wang
Wei Wang
ZYZihui Yang
Zihui Yang
YCYongrok Choi
Yongrok Choi


1 January 2018 in Resources, Conservation and Recycling
Verified
Journal Article
Closed access
WWWei Wang
Wei Wang
HXHualin Xie
Hualin Xie
NZNing Zhang
Ning Zhang
DXDong Xiang
Dong Xiang

31 July 2015 in Sustainability
Verified
Journal Article
Open access
PDF file
Hualin XieHualin Xie
Hualin Xie
WWWei Wang
Wei Wang
Using a sequential slack-based measure (SSBM) model, this paper analyzes the spatiotemporal disparities of urban land use economic efficiency (ULUEE) under environmental constraints, and its influencing factors in 270 cities across China from 2003–2012. The main results are as follows: (1) The average ULUEE for Chinese cities is only 0.411, and out of the 270 cities, only six cities are always efficient in urban land use in the study period. Most cities have a lot of room to improve the economic output of secondary and tertiary industries, as well as environmental protection work; (2) The eastern region of China enjoys the highest ULUEE, followed by the western and central regions. Super-scale cities show the best performance of all four city scales, followed by large-scale, small-scale and medium-scale cities. Cities with relatively developed economies and less pollutant discharge always have better ULUEE; (3) The results of slack variables analysis show that most cities have problems such as the labor surplus, over-development, excessive pollutant discharge, economic output shortage, and unreasonable use of funds is the most serious one; (4) The regression results of the influencing factors show that improvements of the per capita GDP and land use intensity are helpful to raise ULUEE. The urbanization rate and the proportion of foreign enterprises’ output account for the total output in the secondary and tertiary industries only have the same effect in some regions and city scales. The land management policy and land leasing policy have negative impact on the ULUEE in all the three regions and four city scales; (5) Some targeted policy goals are proposed, including the reduction of surplus labor, and pay more attention to environmental protection. Most importantly, effective implementation of land management policies from the central government, and stopping blind leasing of land to make up the local government’s financial deficit would be very helpful to improve the ULUEE of Chinese cities.

6 April 2016 in Sustainability
Verified
Journal Article
Open access
PDF file
WWWei Wang
Wei Wang
Hualin XieHualin Xie
Hualin Xie
TJTong Jiang
Tong Jiang
DZDaobei Zhang
Daobei Zhang
XXXue Xie
Xue Xie
Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote the sustainable use of industrial land. This paper aims to analyze the dynamic changes in the total-factor carbon emission performance of industrial land use (TCPIL) in China by applying a global directional distance function (DDF) and non-radial Luenberger productivity index. The empirical results show that the eastern region enjoys better TCPIL than the central and western regions, but the regional gaps in TCPIL are narrowing. The growth in NLCPILs (non-radial Luenberger carbon emission performance of industrial land use) in the eastern and central regions is mainly driven by technological progress, whereas efficiency improvements contribute more to the growth of NLCPIL in the western region. The provinces in the eastern region have the most innovative and environmentally-friendly production technologies. The results of the analysis of the influencing factors show implications for improving the NLCPIL, including more investment in industrial research and development (R&D), the implementation of carbon emission reduction policies, reduction in the use of fossil energy, especially coal, in the process of industrial production, actively learning about foreign advanced technology, properly solving the problem of surplus labor in industry and the expansion of industrial development.