弹性(材料科学)
业务
经济
环境经济学
物理
热力学
作者
Rabindra Nepal,Xiaomeng Zhao,Kangyin Dong,Jianda Wang,Arshian Sharif
出处
期刊:Energy Economics
[Elsevier BV]
日期:2024-12-25
卷期号:142: 108159-108159
被引量:51
标识
DOI:10.1016/j.eneco.2024.108159
摘要
Energy systems are very fragile and vulnerable to various external shocks, so improving their resilience enables them to cope better. An important channel for building energy resilience is Artificial Intelligence (AI) technology, which provides innovative avenues for addressing this challenge. This study uses data from a balanced panel of 30 Chinese provinces from 2006 to 2019 to empirically evaluate how AI technology advancement affects China's energy resilience. Our study also examines the heterogeneity and possible impact mechanisms. The results show that AI technology innovation can effectively promote energy resilience. The study conducts several robustness checks to confirm the validity of this finding. However, this facilitation varies by region, with the highest effect in the central area, followed by the eastern and western regions. Moreover, the advancement of green finance is developed through AI technology innovation, which indirectly enhances energy resilience. This study aims to analyze the ability to improve energy systems' resilience through AI technology innovation, which provides valuable lessons for policymakers. • We analyze the interaction between Artificial Intelligence (AI) technology innovation and energy resilience. • The advancement of AI technology innovation c raises the bar for energy resilience. • Regional heterogeneity in the effect of AI technology innovation on energy resilience exists. • The impact on energy resilience increases with the extent of innovation development in AI technology innovation. • Green finance can be treated as a positive mediating variable.
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