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The Impact of Artificial Intelligence on Load Capacity Factor in the G20

Dados Bibliográficos

ID16914014
AutoresHongjie Luo (0009-0003-7362-5917, Universiti Putra Malaysia, autor correspondente), Ying Sun (0009-0008-7911-9034, Fuzhou University), Jia Li (0000-0003-0253-8544, Eastern Liaoning University), Fakarudin Kamarudin (0000-0001-8180-1173, Universiti Putra Malaysia), Arum Setyowati (0000-0002-5280-1470, Sebelas Maret University)
Ano2025
Volume15
Fascículo4
Data de publicação2025-10-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoSAGE Open (JOURNAL)
Identificadores do periódicoISSN: 2158-2440 • E-ISSN: 2158-2440
EditoraSAGE Publications (PUBLISHER • US)
DOI10.1177/21582440251386911
OpenAlexW4415386800
IdiomaEN
Referências citadas82

This study investigated the impact of artificial intelligence on the load capacity factor. Based on data collected from G20 countries from 1998 to 2017, the basic results indicated that artificial intelligence reduced the load capacity factor. The impact of artificial intelligence was also less noticeable in nations with higher load capacity factors, as shown by the quantile regression studies. The robust tests confirmed the negative influence. Moreover, intellectual property rights lessened the effect of artificial intelligence on the environment. Economic growth played a mediating role in the nexus between artificial intelligence and the environment. The influence of artificial intelligence on the environment increased when the share of urbanization rose above the threshold of 84.1%. Several policy implications were then proposed by the study in light of these findings

Artificial Intelligence System · Quantile · Quantile regression · Urbanization · Energy, Environment, Economic Growth · Market Dynamics and Volatility · Monetary Policy and Economic Impact

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