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Artificial Intelligence in Energy Economics Research: A Bibliometric Review

Author

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  • Zhilun Jiao

    (College of Economic and Social Development, Nankai University, Tianjin 300071, China
    The Laboratory of Behavioral Economics and Policy Simulation, Nankai University, Tianjin 300071, China)

  • Chenrui Zhang

    (College of Economic and Social Development, Nankai University, Tianjin 300071, China)

  • Wenwen Li

    (College of Economic and Social Development, Nankai University, Tianjin 300071, China)

Abstract

Artificial intelligence (AI) is gaining attention in energy economics due to its ability to process large-scale data as well as to make non-linear predictions and is providing new development opportunities and research subjects for energy economics research. The aim of this paper is to explore the trends in the application of AI in energy economics over the decade spanning 2014–2024 through a systematic literature review, bibliometrics, and network analysis. The analysis of the literature shows that the prominent research themes are energy price forecasting, AI innovations in energy systems, socio-economic impacts, energy transition, and climate change. Potential future research directions include energy supply-chain resilience and security, social acceptance and public participation, economic inequality and the technology gap, automated methods for energy policy assessment, the circular economy, and the digital economy. This innovative study contributes to a systematic understanding of AI and energy economics research from the perspective of bibliometrics and inspires researchers to think comprehensively about the research challenges and hotspots.

Suggested Citation

  • Zhilun Jiao & Chenrui Zhang & Wenwen Li, 2025. "Artificial Intelligence in Energy Economics Research: A Bibliometric Review," Energies, MDPI, vol. 18(2), pages 1-30, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:2:p:434-:d:1570956
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    References listed on IDEAS

    as
    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Düsterhöft, Maximilian & Schiemann, Frank & Walther, Thomas, 2023. "Let’s talk about risk! Stock market effects of risk disclosure for European energy utilities," Energy Economics, Elsevier, vol. 125(C).
    3. Weishu Liu, 2019. "The data source of this study is Web of Science Core Collection? Not enough," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1815-1824, December.
    4. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    5. Kocaarslan, Baris & Mushtaq, Rizwan, 2024. "The impact of liquidity conditions on the time-varying link between U.S. municipal green bonds and major risky markets during the COVID-19 crisis: A machine learning approach," Energy Policy, Elsevier, vol. 184(C).
    6. Xu Gong & Mengjie Li & Keqin Guan & Chuanwang Sun, 2023. "Climate change attention and carbon futures return prediction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1261-1288, September.
    7. Gozgor, Giray & Paramati, Sudharshan Reddy, 2022. "Does energy diversification cause an economic slowdown? Evidence from a newly constructed energy diversification index," Energy Economics, Elsevier, vol. 109(C).
    8. Wang, Bo & Wang, Jianda & Dong, Kangyin & Nepal, Rabindra, 2024. "How does artificial intelligence affect high-quality energy development? Achieving a clean energy transition society," Energy Policy, Elsevier, vol. 186(C).
    9. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    10. Dimou, Andreas & Vakalis, Stergios, 2022. "Technoeconomic analysis of green energy transitions in isolated grids: The case of Ai Stratis – Green Island," Renewable Energy, Elsevier, vol. 195(C), pages 66-75.
    11. Lutz Kilian & Robert J. Vigfusson, 2017. "The Role of Oil Price Shocks in Causing U.S. Recessions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1747-1776, December.
    12. Čábelková, Inna & Strielkowski, Wadim & Streimikiene, Dalia & Cavallaro, Fausto & Streimikis, Justas, 2021. "The social acceptance of nuclear fusion for decision making towards carbon free circular economy: Evidence from Czech Republic," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    13. Guo, Lili & Huang, Xinya & Li, Yanjiao & Li, Houjian, 2023. "Forecasting crude oil futures price using machine learning methods: Evidence from China," Energy Economics, Elsevier, vol. 127(PA).
    14. Shahbaz, Muhammad & Siddiqui, Aaliyah & Ahmad, Shabbir & Jiao, Zhilun, 2023. "Financial development as a new determinant of energy diversification: The role of natural capital and structural changes in Australia," Energy Economics, Elsevier, vol. 126(C).
    15. Hanyao Gao & Gang Kou & Haiming Liang & Hengjie Zhang & Xiangrui Chao & Cong-Cong Li & Yucheng Dong, 2024. "Machine learning in business and finance: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-35, December.
    16. Thakur, Jagruti & Hesamzadeh, Mohammad Reza & Date, Paresh & Bunn, Derek, 2023. "Pricing and hedging wind power prediction risk with binary option contracts," Energy Economics, Elsevier, vol. 126(C).
    17. Zhong, Yufei & Chen, Xuesheng & Wang, Zhixian & Lin, Regina Fang-Ying, 2024. "The nexus among artificial intelligence, supply chain and energy sustainability: A time-varying analysis," Energy Economics, Elsevier, vol. 132(C).
    18. Neto-Bradley, André Paul & Choudhary, Ruchi & Bazaz, Amir, 2020. "Slipping through the net: Can data science approaches help target clean cooking policy interventions?," Energy Policy, Elsevier, vol. 144(C).
    19. Chishti, Muhammad Zubair & Sinha, Avik & Zaman, Umer & Shahzad, Umer, 2023. "Exploring the dynamic connectedness among energy transition and its drivers: Understanding the moderating role of global geopolitical risk," Energy Economics, Elsevier, vol. 119(C).
    20. Maruejols, Lucie & Höschle, Lisa & Yu, Xiaohua, 2022. "Vietnam between economic growth and ethnic divergence: A LASSO examination of income-mediated energy consumption," Energy Economics, Elsevier, vol. 114(C).
    21. Bennedsen, Mikkel & Hillebrand, Eric & Jensen, Sebastian, 2023. "A neural network approach to the environmental Kuznets curve," Energy Economics, Elsevier, vol. 126(C).
    22. Zhao, Congyu & Dong, Kangyin & Wang, Kun & Nepal, Rabindra, 2024. "How does artificial intelligence promote renewable energy development? The role of climate finance," Energy Economics, Elsevier, vol. 133(C).
    23. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).
    24. Wang, Zongrun & Zhang, Taiyu & Ren, Xiaohang & Shi, Yukun, 2024. "AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies," Energy Economics, Elsevier, vol. 132(C).
    25. Anca Gabriela Ilie & Marinela Luminita Emanuela Zlatea & Cristina Negreanu & Dan Dumitriu & Alma Pentescu, 2023. "Reliance on Russian Federation Energy Imports and Renewable Energy in the European Union," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(64), pages 780-780, August.
    26. Zhong, Wenli & Liu, Yang & Dong, Kangyin & Ni, Guohua, 2024. "Assessing the synergistic effects of artificial intelligence on pollutant and carbon emission mitigation in China," Energy Economics, Elsevier, vol. 138(C).
    27. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    28. Sinha, Avik & Bekiros, Stelios & Hussain, Nazim & Nguyen, Duc Khuong & Khan, Sana Akbar, 2023. "How social imbalance and governance quality shape policy directives for energy transition in the OECD countries?," Energy Economics, Elsevier, vol. 120(C).
    29. Zhang, Xiaojing & Khan, Khalid & Shao, Xuefeng & Oprean-Stan, Camelia & Zhang, Qian, 2024. "The rising role of artificial intelligence in renewable energy development in China," Energy Economics, Elsevier, vol. 132(C).
    30. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    31. 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).
    32. Mangla, Sachin Kumar & Srivastava, Praveen Ranjan & Eachempati, Prajwal & Tiwari, Aviral Kumar, 2024. "Exploring the impact of key performance factors on energy markets: From energy risk management perspectives," Energy Economics, Elsevier, vol. 131(C).
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