Mechanism conflicts: carbon reduction pathways and optimization in China’s Big Data Policy DOI Creative Commons

Bihua Zhou,

Yun Huang, Hang Su

и другие.

Humanities and Social Sciences Communications, Год журнала: 2025, Номер 12(1)

Опубликована: Апрель 21, 2025

Язык: Английский

Unveiling the Environmental Implications of China’s Industrial Robots: Empirical Investigation and Mechanism Discussion DOI Creative Commons
Miaomiao Tao, Sihong Wu

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144897 - 144897

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Breaking the inertia of traditional economic development: Does network infrastructure construction achieve urban carbon unlocking? DOI
Weiliang Tao, Shimei Weng, Xueli Chen

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106197 - 106197

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Digital Transformation and Carbon Emission Reduction: The Moderating Effect of External Pressure and Support DOI

Shaozhen Han,

Hanfeng Zhang,

Hui Li

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145108 - 145108

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Research on the impact of green finance on collaborative governance of pollution reduction and carbon reduction DOI Creative Commons
Ke Lu, Dongri Han, Chaoyang Li

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 18, 2025

Collaborative governance of pollution reduction and carbon is an important measure to achieve the goal "green ecological civilization construction" in China. This paper utilizes coupling coordination degree model assess level collaborative reduction, while entropy method employed quantify green finance development index. Using provincial panel data from 2013 2022 China, this initially explores direct relationship between through a baseline regression model. Secondly, considering heterogeneity geographical location energy endowment, categorizes sample provinces into distinct regions conduct heterogeneous analysis. Lastly, employing threshold model, examines non-linear impact on with finance, technology innovation, new industry as variables. The following results are obtained test: (1) Green significantly directly impacts reduction. (2) effect varies by showing pattern "Central > Western Eastern Northeast" "Energy-rich areas Non-energy-rich areas." (3) Considering regional heterogeneity, exhibits varying effects In case low level, high development, can have more positive influence. study offer certain reference value for government formulate relevant policies create good environment.

Язык: Английский

Процитировано

0
Mechanism conflicts: carbon reduction pathways and optimization in China’s Big Data Policy DOI Creative Commons

Bihua Zhou,

Yun Huang, Hang Su

и другие.

Humanities and Social Sciences Communications, Год журнала: 2025, Номер 12(1)

Опубликована: Апрель 21, 2025

Язык: Английский

Процитировано

0