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Corrigendum to “Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement” [Energy Economics Volume 131, March 2024, 107388]

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  • Chishti, Muhammad Zubair
  • Xia, Xiqiang
  • Dogan, Eyup

Abstract

This study contributes to the existing literature by investigating and confirming a range of diverse outcomes related to the interplay of factors shaping the global energy transition (ET). Employing advanced methodologies, including the extension of the QVAR technique to short-term (SR), medium-term (MR), and long-term (LR) connectedness analysis, as well as the application of the CQ method to explore relationships within varying market conditions and timeframes, the study examines the interconnectedness of critical variables: artificial intelligence (AI), the Belt and Road Initiative (BRI), the Paris Agreement (PA), green technologies (GT), geopolitical risk (GPR), and ET. The findings highlight several crucial insights. Firstly, all selected variables demonstrate substantial interconnectedness across different time horizons, except for MR, which exhibits comparatively weaker connectedness than SR and LR. Secondly, independent series reveal diverse impacts on ET across various market conditions and periods. For example, in SR, most series produce mixed effects on ET, with BRI having primarily adverse consequences and GPR predominantly yielding positive impacts. In MR, the influence of AI, PA, and GT on ET varies, while BRI enhances ET, and GPR essentially hampers it. Notably, in LR, AI, BRI, PA, and GT significantly promote ET, while GPR disrupts its progress. Additionally, the study underscores the dynamic and time-varying nature of the relationships between AI, BRI, PA, GT, GPR, and ET across different market conditions, thus holding essential implications for shaping global policies to foster sustainable energy transitions.
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Suggested Citation

  • Chishti, Muhammad Zubair & Xia, Xiqiang & Dogan, Eyup, 2025. "Corrigendum to “Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement” [Energy Economics Volume 131, March 2024, 107388]," Energy Economics, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:eneeco:v:142:y:2025:i:c:s0140988324008788
    DOI: 10.1016/j.eneco.2024.108169
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    2. Chishti, Muhammad Zubair & Dogan, Eyup & Binsaeed, Rima H., 2024. "Can artificial intelligence and green finance affect economic cycles?," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    3. Lee, Chien-Chiang & Li, Jiangnan & Yan, Jingyang, 2025. "Can artificial intelligence contribute to the new energy system? Based on the perspective of labor supply," Technology in Society, Elsevier, vol. 81(C).
    4. Feng, Lingbing & Qi, Jiajun & Zheng, Yuhao, 2025. "How can AI reduce carbon emissions? Insights from a quasi-natural experiment using generalized random forest," Energy Economics, Elsevier, vol. 141(C).
    5. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).
    6. Niu, Niu & Ma, Junhua & Zheng, Deyuan & Lu, Yang & Zhang, Bin, 2025. "Extreme weather and the green transition of energy firms: The moderating effect of digital technology and digital inclusive finance," Research in International Business and Finance, Elsevier, vol. 76(C).
    7. Marwan Al‐Raeei, 2025. "The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(1), pages 508-517, February.
    8. Xu, Juan & Chen, Yu & Yang, Nan & Shao, Shuai, 2025. "The impact of artificial intelligence on the energy transition: evidence from Chinese cities," World Development, Elsevier, vol. 195(C).
    9. Zou, Tong & Li, Fanrong & Guo, Pibin, 2024. "Advancing effective energy transition: The effects and mechanisms of China's dual-pilot energy policies," Energy, Elsevier, vol. 307(C).
    10. Niu, Xiaotong & Lin, Changao & He, Shanshan & Yang, Youcai, 2025. "Artificial intelligence and enterprise pollution emissions: From the perspective of energy transition," Energy Economics, Elsevier, vol. 144(C).
    11. Gao, Xiangming & Ji, Xinliang & Wang, Rong & Yu, Jian, 2025. "The effect of artificial intelligence on energy transition: Evidence from China," Energy Economics, Elsevier, vol. 147(C).
    12. Tang, Pengzhu & Ma, Houyun & Sun, Yuanyuan & Xu, Xiaowan, 2024. "Exploring the role of Fintech, Green Finance and Natural Resources towards Environmental Sustainability: A study on ASEAN economies," Resources Policy, Elsevier, vol. 94(C).
    13. Fang Yang & Juan Li, 2024. "A Review of Renewable Energy Investment in Belt and Road Initiative Countries: A Bibliometric Analysis Perspective," Energies, MDPI, vol. 17(19), pages 1-24, September.
    14. Sivasubramanian Manikandan & Rangarajan Sindhu Kaviya & Dhamodharan Hemnath Shreeharan & Ramasamy Subbaiya & Sundaram Vickram & Natchimuthu Karmegam & Woong Kim & Muthusamy Govarthanan, 2025. "Artificial intelligence‐driven sustainability: Enhancing carbon capture for sustainable development goals– A review," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(2), pages 2004-2029, April.
    15. Shuhong Peng & Jing Qian & Xiuwei Xing & Jing Wang & Aliya Adeli & Shujie Wei, 2025. "Technological Cooperation for Sustainable Development Under the Belt and Road Initiative and the Sustainable Development Goals: Opportunities and Challenges," Sustainability, MDPI, vol. 17(2), pages 1-27, January.
    16. Dong, Zequn & Tan, Chaodan & Ma, Biao & Ning, Zhaoshuo, 2024. "The impact of artificial intelligence on the energy transition: The role of regulatory quality as a guardrail, not a wall," Energy Economics, Elsevier, vol. 140(C).
    17. Li, Lingxiao & Wen, Jun & Li, Yan & Mu, Zi, 2025. "Supply chain challenges and energy insecurity: The role of AI in facilitating renewable energy transition," Energy Economics, Elsevier, vol. 144(C).
    18. Boyu Yuan & Runde Gu & Peng Wang & Yuwei Hu, 2025. "How Does New Quality Productive Forces Affect Green Total Factor Energy Efficiency in China? Consider the Threshold Effect of Artificial Intelligence," Sustainability, MDPI, vol. 17(15), pages 1-21, August.
    19. Jiao, Anqi & Lu, Juntai & Ren, Honglin & Wei, Jia, 2024. "The role of AI capabilities in environmental management: Evidence from USA firms," Energy Economics, Elsevier, vol. 134(C).
    20. Wu, Xiuqin & Zhang, Yi & Lee, Chi-Chuan, 2025. "Driving low-carbon energy transition with FinTech: The role of government environmental attention," Energy, Elsevier, vol. 330(C).
    21. Chishti, Muhammad Zubair & Xia, Xiqiang & Du, Anna Min & Özkan, Oktay, 2025. "Digital financial inclusion, the belt and road initiative, and the Paris agreement: Impacts on energy transition grid costs," Finance Research Letters, Elsevier, vol. 72(C).
    22. Lee, Chien-Chiang & Wang, Tianhui, 2024. "The impact of renewable energy policies on the energy transition -– An empirical analysis of Chinese cities," Energy Economics, Elsevier, vol. 138(C).

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