Optimal Strategy of Artificial Intelligence on Low-Carbon Energy Transformation: Perspective from Enterprise Green Technology Innovation Efficiency DOI
Mingtao Zhao, Xuebao Fu,

Jun Sun

et al.

Published: Jan. 1, 2024

Language: Английский

Digital brains, green gains: Artificial intelligence's path to sustainable transformation DOI Creative Commons
Miaomiao Tao

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

Published: Oct. 2, 2024

Language: Английский

Citations

9
The Impact of Innovation-Driven Industrial Clusters on Urban Carbon Emission Efficiency: Empirical Evidence from China DOI
Hongyu Lu,

Zhuang Yao,

Zhao Cheng

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106220 - 106220

Published: Feb. 1, 2025

Language: Английский

Citations

1
Impact of Digitization and Artificial Intelligence on Carbon Emissions Considering Variable Interaction and Heterogeneity: An Interpretable Deep Learning Modeling Framework DOI

Gongquan Zhang,

Shenglin Ma, Mingxing Zheng

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106333 - 106333

Published: March 1, 2025

Language: Английский

Citations

1
Can artificial intelligence improve enterprise environmental performance: Evidence from China DOI

Junkai Wang,

Andong Wang,

Kaijie Luo

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 123079 - 123079

Published: Oct. 30, 2024

Language: Английский

Citations

6
The impact of artificial intelligence on carbon market in China: Evidence from quantile-on-quantile regression approach DOI

Wei Jiang,

Yanhui Hu, Xiangyu Zhao

et al.

Technological Forecasting and Social Change, Journal Year: 2025, Volume and Issue: 212, P. 123973 - 123973

Published: Jan. 15, 2025

Language: Английский

Citations

0
The Effect of Intelligent Development on Green Economy Efficiency: An Analysis Based on China’s Province-Level Data DOI Open Access
Yingyu Yao,

Haiying Pan

Sustainability, Journal Year: 2025, Volume and Issue: 17(2), P. 678 - 678

Published: Jan. 16, 2025

As the main driving force of new technological revolution, intelligent development is key to promoting high-quality economic development. This paper empirically examines nonlinear influence on green economy efficiency and its action paths using provincial panel data China from 2009 2021. The result provides significant evidence a U-shaped relationship between efficiency, indicating that initially leads decreases before ultimately increasing. Additional analysis confirms environmental regulation, finance, industrial agglomeration positively moderate impact efficiency. Furthermore, heterogeneous tests reveal in eastern region after release “Made 2025” 2015, effect more pronounced. findings this provide beneficial reference for how leverage technology kinetic energy growth under concept.

Language: Английский

Citations

0
Optimal strategy of artificial intelligence on low-carbon energy transformation: Perspective from enterprise green technology innovation efficiency DOI
Mingtao Zhao, Xuebao Fu,

Jun Sun

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135035 - 135035

Published: Feb. 1, 2025

Language: Английский

Citations

0
Digital Technology and AI for Smart Sustainable Cities in the Global South: A Critical Review of Literature and Case Studies DOI Creative Commons
Dillip Kumar Das

Urban Science, Journal Year: 2025, Volume and Issue: 9(3), P. 72 - 72

Published: March 5, 2025

Many countries across the Global South strive to align their urban development with sustainability goals. Consequently, notion of smart sustainable cities has emerged, integrating ideas and sustainability. The region faces diverse challenges, including rapid population growth financial constraints. Infrastructural deficiencies, especially in digital infrastructure AI adoption, add these challenges. Therefore, exploring technologies is essential for developing smart, South. This paper examined both potential barriers AI. It also explored policy implications proposes a framework cities. A qualitative methodological approach used, systematic literature review case studies. study demonstrates how various challenges can be addressed AI, alongside adoption. conceptual three key pillars: adopting as pivotal element, overcoming barriers, identifying application areas transform into Moreover, discusses suggests future directions research.

Language: Английский

Citations

0
Industrial intelligence and marine pollution in coastal cities: A Chinese city-level study DOI

Jiayu Tian,

Xie Jie

Ocean & Coastal Management, Journal Year: 2025, Volume and Issue: 264, P. 107621 - 107621

Published: March 15, 2025

Language: Английский

Citations

0
Improving Corporate Environmental Performance Through Big Data Analytics Implementation: The Role of Industry Environment DOI Open Access

Ahmed Alyahya,

Gomaa Agag

Sustainability, Journal Year: 2025, Volume and Issue: 17(7), P. 2928 - 2928

Published: March 26, 2025

Big data analytics (BDA) has recently received significant public interest and is widely considered as a transformative technology set to improve organizations’ environmental performance. However, prior empirical studies have yielded inconsistent findings. Based on organizational learning theory, our paper utilized longitudinal approach understand the relationships between big implementation corporate This project also investigates role of industry environment in influencing these relationships. employed from 172 firms covering 2408 firm-year observations Fortune 200 firms. We “the generalized method moments (GMMs) technique” test study assumptions. Our analysis shows that one-unit improvement BDA leads to, average, 2.8% performance (CEP). In addition, impact CEP greater more complex dynamic settings. offers meaningful implications for scholars managers influence across various Moreover, this provides refined comprehension ramifications BDA, consequently addressing essential enquiries how when can

Language: Английский

Citations

0