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Does the lack of energy resilience a serious problem at the forefront of policy analysts? Role of supply chain digitalization and environmental law in OECD countries

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  • Du, Xu
  • Fang, Shuanxi

Abstract

Energy efficiency improvements leading to cleaner output have recently emerged as a hot topic in sustainable development research. At this time, OECD nations are not generating enough money to guarantee that energy efficiency measures can be purchased. Artificial intelligence (AI) is causing a revolution in optimizing energy efficiency by allowing for sophisticated analysis and management of energy systems. Thus, in this stage of digital economic growth, energy resilience might be impacted by the fast development of AI technology, the energy internet, and other emerging forms of the network economy. This study aims to analyze the effects of digitalization in the supply chain, artificial intelligence, and finance on energy resilience (ENR) in seventeen OECD countries by using panel data from 2006 to 2021. Three dynamic panel data models are employed: one-step difference GMM, one-step system GMM, and two-step system GMM. The findings show that population growth and tax environmental regulations decrease energy resilience in OECD countries. On the other hand, digitalization of the supply chain, advancements in finance, and AI have increased energy resilience. Moreover, the study uses SQR and panel quantile regression (PQR) tests to ensure that the dynamic panel model is robust. Based on the findings, significant policy implications are proposed to enhance energy quality in OECD nations. Finally, AI has enormous potential to improve energy efficiency by facilitating more innovative optimization and management of energy systems. Organizations may save much money, cut expenses, and help build a better energy future by using AI to save energy.

Suggested Citation

  • Du, Xu & Fang, Shuanxi, 2025. "Does the lack of energy resilience a serious problem at the forefront of policy analysts? Role of supply chain digitalization and environmental law in OECD countries," Energy Economics, Elsevier, vol. 141(C).
    • Handle: RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324008594
    DOI: 10.1016/j.eneco.2024.108150
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    3. Wang, Chang-song & Chen, Wei & Zheng, Yang & Dai, Qin, 2025. "Bridge the gap: nexus between artificial intelligence and urban energy resilience, evidence from low-carbon city in China," Energy Economics, Elsevier, vol. 152(C).

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