The influence mechanism of internal and external driving factors on corporate green behavior DOI Creative Commons
Chuang Li, Yunlong Wang,

Linan Ye

и другие.

Ecological Indicators, Год журнала: 2024, Номер 169, С. 112937 - 112937

Опубликована: Дек. 1, 2024

Язык: Английский

Study on calculation and optimization path of energy utilization efficiency of provincial logistics industry in China DOI
Chuang Li, Yunlong Wang,

Zhiyuan Li

и другие.

Renewable Energy, Год журнала: 2025, Номер unknown, С. 122594 - 122594

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Driving Mechanism of Synergistic Efficiency in Reducing Pollution and Carbon: Evidence From 249 Green Parks DOI Open Access
Chuang Li, Keke Li,

Liping Wang

и другие.

Geological Journal, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

ABSTRACT The green park serves as a significant spatial carrier for China's strategy to become manufacturing powerhouse and promote industrial transformation upgrading. It is crucial platform implementing driving the development of manufacturing, promoting harmonious coexistence between man nature in current era. main focus this study total 249 parks announced by Ministry Industry Information Technology, it employs multi‐time point PSM‐DID method investigate 280 prefecture‐level cities. results show that: (1) coefficient certification policy estimated have significantly negative impact at 1% significance level. (2) facilitates integration pollution reduction carbon efforts leveraging technology innovation government support. (3) effect has regional consistency resource heterogeneity. Therefore, great effects pathways on synergies reduction.

Язык: Английский

Процитировано

0

Spatiotemporal Patterns and Influencing Factors of Carbon Emissions in the Yangtze River Basin: A Shrinkage Perspective DOI Open Access
Xiu‐Juan Jiang,

Jingyuan Sun,

Jinchuan Huang

и другие.

Sustainability, Год журнала: 2025, Номер 17(5), С. 2112 - 2112

Опубликована: Фев. 28, 2025

This study categorizes 45 cities into four types based on population dynamics using census data (2000–2020). Methods such as ArcGIS10.8, carbon emission estimation, LISA clustering, and association analysis are employed to explore the spatiotemporal distribution of shrinking emissions. analyzes patterns influencing factors for city provides policy recommendations. The findings follows: (1) Lasting-growth show a “two-end mass, middle-point” pattern, while stage-growth stage-shrinking “point” distributed. Lasting-shrinking mainly distributed in middle lower reaches Yangtze River. (2) Total emissions rising, showing two clusters high-value areas. Carbon intensity is falling quickly, being higher west east. (3) have fastest direct growth rate, energy-related indirect undergoing increase rate other In terms reduction, lasting-growth perform best, whereas worst. (4) Regional GDP, per capita regional urban construction area, hospital beds 10,000 people promote reduction types, number industrial enterprises inhibits it. Birth aging mortality no significant impact. addresses gaps previous research by considering dynamic nature processes analyzing patterns.

Язык: Английский

Процитировано

0

Do green investments really make companies “green”? Empirical evidence from corporate ESG ratings DOI
Ming Zhang, Xueli Zhang, Yan Song

и другие.

Environment Development and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Март 28, 2025

Язык: Английский

Процитировано

0

The influence mechanism of internal and external driving factors on corporate green behavior DOI Creative Commons
Chuang Li, Yunlong Wang,

Linan Ye

и другие.

Ecological Indicators, Год журнала: 2024, Номер 169, С. 112937 - 112937

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2