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Research on carbon emission efficiency in the Chinese construction industry based on a three-stage DEA-Tobit model
by
Zhang, Mengna
, Li, Lianshui
, Cheng, Zhonghua
in
Aquatic Pollution
/ Atmospheric Protection/Air Quality Control/Air Pollution
/ Carbon
/ Carbon - analysis
/ China
/ Construction Industry
/ Data envelopment analysis
/ Earth and Environmental Science
/ Ecotoxicology
/ Efficiency
/ Emissions
/ energy
/ Environment
/ Environmental Chemistry
/ Environmental factors
/ Environmental Health
/ Environmental science
/ Industrial Development
/ industrialization
/ Interference
/ labor force
/ Optimization
/ Regional differences
/ regression analysis
/ Research Article
/ Scale efficiency
/ Technological change
/ technology
/ Waste Water Technology
/ Water Management
/ Water Pollution Control
2021
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Research on carbon emission efficiency in the Chinese construction industry based on a three-stage DEA-Tobit model
by
Zhang, Mengna
, Li, Lianshui
, Cheng, Zhonghua
in
Aquatic Pollution
/ Atmospheric Protection/Air Quality Control/Air Pollution
/ Carbon
/ Carbon - analysis
/ China
/ Construction Industry
/ Data envelopment analysis
/ Earth and Environmental Science
/ Ecotoxicology
/ Efficiency
/ Emissions
/ energy
/ Environment
/ Environmental Chemistry
/ Environmental factors
/ Environmental Health
/ Environmental science
/ Industrial Development
/ industrialization
/ Interference
/ labor force
/ Optimization
/ Regional differences
/ regression analysis
/ Research Article
/ Scale efficiency
/ Technological change
/ technology
/ Waste Water Technology
/ Water Management
/ Water Pollution Control
2021
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Research on carbon emission efficiency in the Chinese construction industry based on a three-stage DEA-Tobit model
by
Zhang, Mengna
, Li, Lianshui
, Cheng, Zhonghua
in
Aquatic Pollution
/ Atmospheric Protection/Air Quality Control/Air Pollution
/ Carbon
/ Carbon - analysis
/ China
/ Construction Industry
/ Data envelopment analysis
/ Earth and Environmental Science
/ Ecotoxicology
/ Efficiency
/ Emissions
/ energy
/ Environment
/ Environmental Chemistry
/ Environmental factors
/ Environmental Health
/ Environmental science
/ Industrial Development
/ industrialization
/ Interference
/ labor force
/ Optimization
/ Regional differences
/ regression analysis
/ Research Article
/ Scale efficiency
/ Technological change
/ technology
/ Waste Water Technology
/ Water Management
/ Water Pollution Control
2021
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Research on carbon emission efficiency in the Chinese construction industry based on a three-stage DEA-Tobit model
Journal Article
Research on carbon emission efficiency in the Chinese construction industry based on a three-stage DEA-Tobit model
2021
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Overview
The traditional data envelopment analysis (DEA) model usually ignores the influence of external environmental factors and random interference. This can easily lead to deviations in efficiency estimates. In order to solve this problem, a three-stage DEA model was used to better reflect the carbon emission efficiency of Chinese construction industry (CEECI) (2006–2017) from the perspective of non-management factors. The internal influencing factors of CEECI are analyzed by the Tobit model, which provides a more accurate basis for formulating policies. It is found that the CEECI is significantly affected by the GDP, the level of industrialization, the degree of opening-up, technological innovation, and energy structure. After excluding environmental factors and random interference, the average CEECI increased by 16%. The resulting calculations are noteworthy in three aspects. First, there are significant regional differences in the CEECI. Both the multi-polarization phenomenon of CEECI and regional differences also reduced gradually over time. Second, the CEECI can be decomposed into pure carbon emission efficiency (PCEE) and scale efficiency (SE), which is mainly caused by SE. Excluding external environmental factors and random interference will have a specific impact on the CEECI. All the 30 provinces are divided into four categories to analyze the reasons and solutions of the differences in the CEECI in provinces. Third, many factors had inhibitory effects on the CEECI, PCEE, and SE; these included energy structure optimization, labor force number, total power of construct ion equipment, and construction intensity in the construction industry. Nevertheless, the development level of the construction industry did have a significant positive effect.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
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