The spatial spillover impact of artificial intelligence on energy efficiency: Empirical evidence from 278 Chinese cities

Yong Wang, Wenhao Zhao and Xuejiao Ma

Energy, 2024, vol. 312, issue C

Abstract: Within the framework of global sustainable development, improving energy efficiency (EE) is recognized as a crucial strategy to address environmental challenges and foster economic growth. This research employs the Spatial Durbin Model to investigate the spatial spillover effects of advancements in artificial intelligence (AI) technology on EE across 278 Chinese cities. The analysis reveals several key findings: first, the advancement of AI technology significantly enhances urban EE and generates a positive spatial spillover effect across different spatial weight matrices; second, there is a nonlinear, inverted U-shaped relationship between AI levels and urban EE; third, industrial structure upgrades play a significant moderating role in the impact of AI technology on urban EE. These insights not only illuminate the complex role of AI in improving regional EE but also provide critical recommendations for policymakers aiming to enhance urban EE and achieve sustainable development goals.

Keywords: Artificial intelligence; Energy efficiency; Spatial durbin model; Spatial spillover effects; Industrial structure upgrading (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:312:y:2024:i:c:s0360544224032730

DOI: 10.1016/j.energy.2024.133497

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