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Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects

Enhancing energy-environmental efficiency (EEE) is crucial for achieving energy conservation and emission reduction goals. Investigating the mechanism through which green technology innovation (GTI) affects EEE and understanding the role of environmental regulation (ER) in this process provides a th...

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Autores principales: Li, Wei, Xu, Xiaomin, Huang, Shengzhong, Cheng, Tong, Liu, Mengkai, Zhang, Can
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682408/
https://www.ncbi.nlm.nih.gov/pubmed/38012201
http://dx.doi.org/10.1038/s41598-023-47786-2
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author Li, Wei
Xu, Xiaomin
Huang, Shengzhong
Cheng, Tong
Liu, Mengkai
Zhang, Can
author_facet Li, Wei
Xu, Xiaomin
Huang, Shengzhong
Cheng, Tong
Liu, Mengkai
Zhang, Can
author_sort Li, Wei
collection PubMed
description Enhancing energy-environmental efficiency (EEE) is crucial for achieving energy conservation and emission reduction goals. Investigating the mechanism through which green technology innovation (GTI) affects EEE and understanding the role of environmental regulation (ER) in this process provides a theoretical basis for efficient utilization of GTI and ER. This study employs a Dynamic Spatial Durbin Model and utilizes panel data from 2003 to 2017 for 30 Chinese provinces to examine the impact of GTI on EEE in the presence of ER. The empirical results reveal: (1) GTI has a U-shaped impact on EEE, primarily driven by SubGI. (2) GTI’s influence on EEE is predominantly reflected in PTE, also stemming from SubGI. (3) The interaction term between ER and GTI is 0.0022, while the GTI coefficient is − 0.0741, and the GTI quadratic term coefficient is 0.0007, all statistically significant. This implies that ER mitigates the negative impact of GTI on EEE while strengthening its positive effect. These findings provide empirical evidence and policy insights for more effectively utilizing GTI and ER to enhance EEE and achieve energy conservation and emissions reduction goals.
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spelling pubmed-106824082023-11-30 Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects Li, Wei Xu, Xiaomin Huang, Shengzhong Cheng, Tong Liu, Mengkai Zhang, Can Sci Rep Article Enhancing energy-environmental efficiency (EEE) is crucial for achieving energy conservation and emission reduction goals. Investigating the mechanism through which green technology innovation (GTI) affects EEE and understanding the role of environmental regulation (ER) in this process provides a theoretical basis for efficient utilization of GTI and ER. This study employs a Dynamic Spatial Durbin Model and utilizes panel data from 2003 to 2017 for 30 Chinese provinces to examine the impact of GTI on EEE in the presence of ER. The empirical results reveal: (1) GTI has a U-shaped impact on EEE, primarily driven by SubGI. (2) GTI’s influence on EEE is predominantly reflected in PTE, also stemming from SubGI. (3) The interaction term between ER and GTI is 0.0022, while the GTI coefficient is − 0.0741, and the GTI quadratic term coefficient is 0.0007, all statistically significant. This implies that ER mitigates the negative impact of GTI on EEE while strengthening its positive effect. These findings provide empirical evidence and policy insights for more effectively utilizing GTI and ER to enhance EEE and achieve energy conservation and emissions reduction goals. Nature Publishing Group UK 2023-11-27 /pmc/articles/PMC10682408/ /pubmed/38012201 http://dx.doi.org/10.1038/s41598-023-47786-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Li, Wei
Xu, Xiaomin
Huang, Shengzhong
Cheng, Tong
Liu, Mengkai
Zhang, Can
Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects
title Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects
title_full Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects
title_fullStr Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects
title_full_unstemmed Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects
title_short Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects
title_sort assessment of green technology innovation on energy-environmental efficiency in china under the influence of environmental regulation considering spatial effects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682408/
https://www.ncbi.nlm.nih.gov/pubmed/38012201
http://dx.doi.org/10.1038/s41598-023-47786-2
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