Can artificial intelligence technology improve green total factor efficiency in energy utilisation? Empirical evidence from 282 cities in China

Yingji Liu (), Ju Guo (), Fangbing Shen () and Yuegang Song ()
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Yingji Liu: Henan Normal University
Ju Guo: Henan Normal University
Fangbing Shen: Henan Normal University
Yuegang Song: Henan Normal University

Economic Change and Restructuring, 2025, vol. 58, issue 2, No 6, 34 pages

Abstract: Abstract This study empirically examines the effects and mechanisms of AI on green total factor efficiency in energy utilization (GTFEEU) using panel data covering 282 Chinese prefecture-level cities from 2006 to 2021. First, the findings demonstrate that artificial intelligence (AI) can considerably improve GTFEEU. Second, AI enhances GTFEEU through mechanisms of industrial structure upgrading, financial development, and government innovation preference. Third, AI application level is the key determinant of overall GTFEEU, with no significant difference in its impact between resource-based and non-resource-based cities. Furthermore, the effect of AI on improving GTFEEU is more pronounced in large cities than in medium-sized and small cities. Fourth, significant spatial autocorrelation is evident between AI and GTFEEU, and the spatial spillover effect is primarily short-term. This study provides valuable insights for policymakers on the effects and mechanisms of developing AI technology for GTFEEU improvement.

Keywords: Artificial intelligence; Green total factor efficiency in energy utilization; Dual carbon goal; Spatial spillover (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10644-025-09862-7

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