How does artificial intelligence affect high-quality energy development? Achieving a clean energy transition society

Energy Policy, Journal Year: 2024, Volume and Issue: 186, P. 114010 - 114010

Published: Feb. 1, 2024

As China's energy development undergoes a process from qualitative improvements to quantitative changes, high-quality (HED) has become vital strategy of the Chinese government. representative emerging technologies, artificial intelligence (AI) can effectively promote clean transition, strengthen security, and enhance above process. Therefore, this paper explores relationship between AI HED based on gauging index level 30 provinces in China covering 2007–2017. In addition, we use green innovation R&D intensity as mediating variables study indirect effect HED. We further explore threshold digital economy The results indicate that positively affects China; specifically, every 1 % increase will lead 0.032 index. Moreover, indirectly increases by improving intensity. Further, shows influences impact This means have significantly positive areas with developed economy. Finally, provide practical approaches reference suggestions for achieve transition assistance AI.

Language: Английский

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How does artificial intelligence promote renewable energy development? The role of climate finance

Energy Economics, Journal Year: 2024, Volume and Issue: 133, P. 107493 - 107493

Published: March 22, 2024

Scholars, stakeholders, and the government have given significant attention to development of renewable energy in recent times. However, previous research has failed acknowledge potential impact artificial intelligence on advancing development. Drawing insights from a global dataset encompassing 63 countries over period 2000–2019, this paper provides observations regarding influence progress energy, by using Instrumental Variable Generalized Method Moments model. We also explore their asymmetric nexus, mediation effect. Moreover, study explores moderating role climate finance highlights following interesting findings. First, contributes significantly enhanced primary finding holds after two robustness tests changing independent dependent variables. Second, an effect development, nexus is closer with lower levels Thid, works through technology innovation Fourth, presents direct benefits development; simultaneously, plays effective relationship between These findings inspire us propose policy implications promote energy.

Language: Английский

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Is artificial intelligence technology innovation a recipe for low-carbon energy transition? A global perspective

Energy, Journal Year: 2024, Volume and Issue: 300, P. 131539 - 131539

Published: May 5, 2024

Language: Английский

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How does digital government affect natural resource sustainability? A global perspective

Resources Policy, Journal Year: 2024, Volume and Issue: 91, P. 104951 - 104951

Published: March 26, 2024

Language: Английский

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Green innovation and natural resource efficiency: The role of environmental regulations and resource endowment in Chinese cities

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122338 - 122338

Published: Sept. 16, 2024

Language: Английский

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Environmental regulation and the widening inequality in urban green innovation: Evidence from China

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 124181 - 124181

Published: Jan. 20, 2025

Language: Английский

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How does digital infrastructure break the resource curse of cities? Evidence from a quasi-natural experiment in China

Resources Policy, Journal Year: 2023, Volume and Issue: 86, P. 104302 - 104302

Published: Oct. 1, 2023

Language: Английский

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Driving towards net zero emissions: The role of natural resources, government debt and political stability

Resources Policy, Journal Year: 2023, Volume and Issue: 88, P. 104479 - 104479

Published: Dec. 11, 2023

Language: Английский

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Financial resources utilization efficiency in sports infrastructure development, determinant of total factor productivity growth and regional production technology heterogeneity in China

Heliyon, Journal Year: 2024, Volume and Issue: 10(5), P. e26546 - e26546

Published: Feb. 23, 2024

Despite China's heavy investment in sports infrastructure development the last decades, financial resources utilization efficiency (FRUE), regional technological gap (TGR), and total factor productivity change (TFPC) are undiscovered worth investigating. To this end, study employed DEA-SBM, Meta-frontier analysis, Malmquist index on data set of 31 Chinese provinces 3 regions for years 2014–2021 to gauge FRUE, TGR, TFPC development. The results indicate that average FRUE is 0.4859, with a growth potential 51.41% resource Further Eastern region more efficient as compared Central western regions. Beijing, Shanghai, Tibet, Hainan, Guangdong top performers FRUE. Further, value TGR East 0.9787 which higher than (0.4977), Western (0.5821) It indicates eastern contains superior production technology China. Moreover, 1.035 witnessed 3.5% growth, primarily determined by (TC). As TC = 1.0273 EC 0.997. has 1.048, indicating Liaoning, Tianjin, Zhejiang TFP over period. Finally, Kruskal-Wallis test proved statistically significant difference three China

Language: Английский

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Digital brains, green gains: Artificial intelligence's path to sustainable transformation

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122679 - 122679

Published: Oct. 2, 2024

Language: Английский

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