The Impact of Carbon Trading Policy on the Green Innovation Efficiency of Enterprises: Evidence from China DOI Open Access
Shuwen Zhang,

Chenhui Ding,

Chao Liu

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11192 - 11192

Published: Dec. 20, 2024

Improving green innovation efficiency (GIE) is crucial for reducing enterprise carbon emissions and fostering sustainability. Meanwhile. most of the research has not considered micro-level influence trading on GIE. Therefore, objective this paper to assess impact policy (CTP) GIE enterprises its specific mechanism. This uses data from China’s listed 2010 2019 treats 2013 CTP in seven regions as a quasi-natural experiment. The Super-SBM model applied calculate difference-in-difference-in-differences (DDD) method assesses by comparing pre- post-policy efficiencies. results reveal that improves high-carbon emission sectors pilot areas. It primarily boosts increasing environmental attention resource allocation enterprises. significantly promotes non-state-owned (non-SOEs), large-scale enterprises, with strict regulations. Finally, recommendations are made more environmentally friendly sustainable development.

Language: Английский

A Configurational Pathway Analysis of Digital Economy and Green Technology Innovation DOI Open Access
Jing Jiang

Modern Economy, Journal Year: 2025, Volume and Issue: 16(02), P. 284 - 299

Published: Jan. 1, 2025

Language: Английский

Citations

0
Research on the Spatio-Temporal Evolution and Impact of China’s Digital Economy and Green Innovation DOI Creative Commons
Chunshan Zhou, Xiaoli Wei,

Xiangjun Dai

et al.

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 633 - 633

Published: March 17, 2025

It is of great significance to study the impact China’s digital economy on green innovation under present conditions. In this work, panel data were used, and research tools such as entropy method, Markov chain with a spatial probability transition matrix, Durbin model applied analyze temporal evolution in 287 Chinese cities from 2011 2021, exploring influence innovation. The results show that exhibited an upward trend. There was basic pattern consisting “high levels east low west” regarding innovation, aggregation types primarily being “HH” “LH”. Moreover, are relatively stable, neighboring areas influencing local changes. has significant promotional effect well spillover effects; differing influences over time can be used categorize into four groups, most falling within first two categories. Based these findings, relevant countermeasures proposed, seeking further enhance role promoting This work provides basis policy suggestions contribute continuous improvements leveraging effects former latter.

Language: Английский

Citations

0
The Impact of Carbon Trading Policy on the Green Innovation Efficiency of Enterprises: Evidence from China DOI Open Access
Shuwen Zhang,

Chenhui Ding,

Chao Liu

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11192 - 11192

Published: Dec. 20, 2024

Improving green innovation efficiency (GIE) is crucial for reducing enterprise carbon emissions and fostering sustainability. Meanwhile. most of the research has not considered micro-level influence trading on GIE. Therefore, objective this paper to assess impact policy (CTP) GIE enterprises its specific mechanism. This uses data from China’s listed 2010 2019 treats 2013 CTP in seven regions as a quasi-natural experiment. The Super-SBM model applied calculate difference-in-difference-in-differences (DDD) method assesses by comparing pre- post-policy efficiencies. results reveal that improves high-carbon emission sectors pilot areas. It primarily boosts increasing environmental attention resource allocation enterprises. significantly promotes non-state-owned (non-SOEs), large-scale enterprises, with strict regulations. Finally, recommendations are made more environmentally friendly sustainable development.

Language: Английский

Citations

0