Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model DOI Creative Commons
Shanglei Chai, Qiang Li, Siyuan Chen

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 16, 2024

Abstract Evaluating and enhancing the environmental efficiency of power generation industry is an effective approach for addressing challenges climate change pollution. Considering influence external factors stochastic factors, this paper proposes improved three-stage slack-based measure with superefficiency data envelopment analysis (SBM-SE-DEA) model to evaluate in China’s 30 provincial regions during 2015–2021. The integrates DEA model, SBM-DEA SE-DEA while accounting undesirable outputs such as carbon emissions air pollutants. results show that (1) a high proportion renewable energy demonstrate best when considering constraints from However, first stage are evidently overestimated due factors. (2) Rational adjustments economic development level, structure, industrial structure play positive role improving efficiency. resource endowment does not yield expected results. Additionally, provinces higher electricity often bear greater pressure (3) third exhibited stable trend driven by internal except Northeast Central-South regions, most still experienced overestimation stage. Thus, optimizing promoting restructuring, strengthening interregional cooperation coordination imperative.

Language: Английский

Evaluation of the environmental efficiency of China’s power generation industry considering carbon emissions and air pollution: an improved three-stage SBM-SE-DEA model DOI
Qiang Li, Shanglei Chai, Siyuan Chen

et al.

Environment Development and Sustainability, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Language: Английский

Citations

2
Navigating the Path to Sustainable Development: China's Revolution in Renewable Energy Through Technological Innovation and Geopolitical Risk Management DOI
Junhui Li,

Bilal Sajid,

Hamid Raza

et al.

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122598 - 122598

Published: Feb. 1, 2025

Language: Английский

Citations

2
Does provincial green governance promote enterprise green investment? Based on the perspective of government vertical management DOI
Weihong Wang, Xuan Wang

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 396, P. 136519 - 136519

Published: Feb. 20, 2023

Language: Английский

Citations

31
Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry DOI Open Access
Sen Wang, Jinye Li

Sustainability, Journal Year: 2023, Volume and Issue: 15(21), P. 15600 - 15600

Published: Nov. 3, 2023

Digital transformation has become essential in promoting and upgrading enterprise elements reshaping the market’s competitive landscape. However, whether digital can further promote green low-carbon synergistic development is still being determined. Using data from 2008 to 2014 matched between A-share listed enterprises China’s heavily polluting industries industrial pollution emission database (robustness tests were used city panel 2013 2019 overcome timeliness of enterprise-level data), we measured total factor productivity, carbon efficiency, joint reduction efficiency companies. We examined dynamic impact corporate on reduction. The empirical results show that (1) inhibits enterprise’s all-green short term but promotes them long term. improve these three efficiencies by enhancing technology innovation ability optimizing allocation efficiency. (2) A heterogeneity analysis found that, external environment, increase environmental regulation enhances efficiencies; internal improvement competitiveness products strengthens promotion (3) Further research shows run, effect enterprises. This instructive for Chinese achieve green, production.

Language: Английский

Citations

11
Assessing the Static and Dynamic Efficiency of Digital Economy in China: Three Stage DEA–Malmquist Index Based Approach DOI Open Access

Guangdi Zhang,

Yaojun Ye,

Mengya Sun

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(6), P. 5270 - 5270

Published: March 16, 2023

The digital economy, a new economic form, has become an essential development engine in various countries. Recently, less research been conducted on the efficiency of with majority studies instead concentrating industrial size economy. Therefore, to quantify and analyze China’s economy from 2013 2020 both static dynamic perspective, this utilized three-stage DEA model Malmquist index. findings demonstrated that after excluding external environmental factors, scale value, integrated technical pure value all significantly increased. This confirmed factors uniquely influence varies by location, eastern region tending perform best, central worst. decomposition results positive growth trend is primarily due technological advancement. Overall, there lot room for Each province city should combine their own capabilities accelerate construction.

Language: Английский

Citations

5
Measurement of green innovation efficiency in Chinese listed energy-intensive enterprises based on the three stage Super-SBM model DOI Creative Commons
Jiaxi Wu, Shali Wang, Rui Zhang

et al.

International Review of Economics & Finance, Journal Year: 2024, Volume and Issue: unknown, P. 103819 - 103819

Published: Dec. 1, 2024

Language: Английский

Citations

1
Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model DOI Creative Commons
Shanglei Chai, Qiang Li, Siyuan Chen

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 16, 2024

Abstract Evaluating and enhancing the environmental efficiency of power generation industry is an effective approach for addressing challenges climate change pollution. Considering influence external factors stochastic factors, this paper proposes improved three-stage slack-based measure with superefficiency data envelopment analysis (SBM-SE-DEA) model to evaluate in China’s 30 provincial regions during 2015–2021. The integrates DEA model, SBM-DEA SE-DEA while accounting undesirable outputs such as carbon emissions air pollutants. results show that (1) a high proportion renewable energy demonstrate best when considering constraints from However, first stage are evidently overestimated due factors. (2) Rational adjustments economic development level, structure, industrial structure play positive role improving efficiency. resource endowment does not yield expected results. Additionally, provinces higher electricity often bear greater pressure (3) third exhibited stable trend driven by internal except Northeast Central-South regions, most still experienced overestimation stage. Thus, optimizing promoting restructuring, strengthening interregional cooperation coordination imperative.

Language: Английский

Citations

0