The impact of artificial intelligence (AI) technology on carbon emissions performance is considered to be a double-edged sword. The debate is aided by this paper's use of data from 278 Chinese cities from 2009 to 2019 based on the two-way fixed effects, instrumental variables (IVs), spatial Durbin (SDM), mediation effect, and moderating effect model. We find that AI technology not only increases the carbon emission scale, but also has an undesirable impact on carbon emission efficiency, which indicates that the use of AI technology currently does not necessarily improve carbon emission performance. Moreover, AI technology does have the potential to reduce the carbon emission scale and improve carbon emission efficiency through energy transition, though this potential is not reflected in industrial transformation. Finally, the impact of AI technology on carbon emission performance is worsened by the energy industry's investment, suggesting that current investments are not being used to enhance AI applications in the field of energy. This study shows that the role of energy transition is crucial if current AI technologies are to achieve a 'decarbonization effect', and that energy industry investments need to be focused on the penetration of AI technologies to realize its positive effect.
机构:
Wuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R China
City Univ Macau, Fac Humanities & Social Sci, Taipa, Macao, Peoples R ChinaWuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R China
Liu, Jun
Shen, Hengxu
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Nanjing Univ Informat Sci & Technol, Sch Management Sci & Engn, Nanjing 210044, Peoples R ChinaWuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R China
Shen, Hengxu
Chen, Junwei
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机构:
Nanjing Univ Informat Sci & Technol, Sch Management Sci & Engn, Nanjing 210044, Peoples R ChinaWuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R China
Chen, Junwei
Jiang, Xin
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机构:
Jiangsu Co Ltd, China Mobile Commun Grp, Taizhou Branch, Taizhou 212200, Peoples R ChinaWuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R China
Jiang, Xin
Siyal, Abdul Waheed
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机构:
Wuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R ChinaWuxi Univ, Sch Digital Econ & Management, Wuxi 214105, Peoples R China
机构:
Ho Chi Minh City Open Univ, Fac Finance & Banking, Ho Chi Minh City, Vietnam
Univ Econ Ho Chi Minh City UEH, Sch Banking, Ho Chi Minh City, VietnamHo Chi Minh City Open Univ, Fac Finance & Banking, Ho Chi Minh City, Vietnam
Nguyen, Quang Khai
Dang, Van Cuong
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Univ Econ Ho Chi Minh City UEH, Sch Publ Finance, Ho Chi Minh City, VietnamHo Chi Minh City Open Univ, Fac Finance & Banking, Ho Chi Minh City, Vietnam
机构:
Baker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, ItalyBaker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, Italy
Lottini, Fabrizio
Bicchi, Marco
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机构:
Baker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, ItalyBaker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, Italy
Bicchi, Marco
Agnolucci, Andrea
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机构:
Baker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, ItalyBaker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, Italy
Agnolucci, Andrea
Marconcini, Michele
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机构:
Univ Florence, Dept Ind Engn, Via Santa Marta 3, I-50139 Florence, ItalyBaker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, Italy
Marconcini, Michele
Arnone, Andrea
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机构:
Univ Florence, Dept Ind Engn, Via Santa Marta 3, I-50139 Florence, ItalyBaker Hughes, Nuovo Pignone, Via Felice Matteucci 2, I-50127 Florence, Italy
Arnone, Andrea
PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 12D,
2024,