Latent Information in the Evolving Energy Structure DOI Open Access
Boqiang Lin, Yitong Zhu

Journal of Global Information Management, Год журнала: 2024, Номер 32(1), С. 1 - 21

Опубликована: Ноя. 10, 2024

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) Triple-Difference (DDD) models to investigate effects AI. research initially demonstrates AI may exhibit dual attributes constraining structure. Specifically, rapid development tends increase proportion fossil fuel-based electricity generation while optimizing consumption renewable energy. Furthermore, degradation structure stems from surge in AI, which capacity is unable satisfy. Lastly, industrial agglomeration construction digital economy have positive impacts energy; technological innovation aids mitigating negative shocks This study provides new perspective role transition.

Язык: Английский

Technological innovations fuel carbon prices and transform environmental management across Europe DOI Creative Commons
Mehmet Balcılar, Ahmed H. Elsayed, Rabeh Khalfaoui

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 373, С. 123663 - 123663

Опубликована: Дек. 17, 2024

Язык: Английский

Процитировано

1
Electricity Generation from Renewable and Non-Renewable Energy Sources in China: The Role of Environmental Policy Stringency, FDI, and Economic Growth DOI

Chunxun Xiag,

Syed Qasim Raza,

Daniel Balsalobre‐Lorente

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0
Latent Information in the Evolving Energy Structure DOI Open Access
Boqiang Lin, Yitong Zhu

Journal of Global Information Management, Год журнала: 2024, Номер 32(1), С. 1 - 21

Опубликована: Ноя. 10, 2024

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) Triple-Difference (DDD) models to investigate effects AI. research initially demonstrates AI may exhibit dual attributes constraining structure. Specifically, rapid development tends increase proportion fossil fuel-based electricity generation while optimizing consumption renewable energy. Furthermore, degradation structure stems from surge in AI, which capacity is unable satisfy. Lastly, industrial agglomeration construction digital economy have positive impacts energy; technological innovation aids mitigating negative shocks This study provides new perspective role transition.

Язык: Английский

Процитировано

0