Artificial Intelligence in Energy Economics Research: A Bibliometric Review
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 t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/2/434 |
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| author | Zhilun Jiao Chenrui Zhang Wenwen Li |
| author_facet | Zhilun Jiao Chenrui Zhang Wenwen Li |
| author_sort | Zhilun Jiao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2d23867c032245ed93fd62340102e020 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-2d23867c032245ed93fd62340102e0202025-01-24T13:31:28ZengMDPI AGEnergies1996-10732025-01-0118243410.3390/en18020434Artificial Intelligence in Energy Economics Research: A Bibliometric ReviewZhilun Jiao0Chenrui Zhang1Wenwen Li2College of Economic and Social Development, Nankai University, Tianjin 300071, ChinaCollege of Economic and Social Development, Nankai University, Tianjin 300071, ChinaCollege of Economic and Social Development, Nankai University, Tianjin 300071, ChinaArtificial 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.https://www.mdpi.com/1996-1073/18/2/434artificial intelligenceenergy economicsbibliometric analysisnetwork analysis |
| spellingShingle | Zhilun Jiao Chenrui Zhang Wenwen Li Artificial Intelligence in Energy Economics Research: A Bibliometric Review Energies artificial intelligence energy economics bibliometric analysis network analysis |
| title | Artificial Intelligence in Energy Economics Research: A Bibliometric Review |
| title_full | Artificial Intelligence in Energy Economics Research: A Bibliometric Review |
| title_fullStr | Artificial Intelligence in Energy Economics Research: A Bibliometric Review |
| title_full_unstemmed | Artificial Intelligence in Energy Economics Research: A Bibliometric Review |
| title_short | Artificial Intelligence in Energy Economics Research: A Bibliometric Review |
| title_sort | artificial intelligence in energy economics research a bibliometric review |
| topic | artificial intelligence energy economics bibliometric analysis network analysis |
| url | https://www.mdpi.com/1996-1073/18/2/434 |
| work_keys_str_mv | AT zhilunjiao artificialintelligenceinenergyeconomicsresearchabibliometricreview AT chenruizhang artificialintelligenceinenergyeconomicsresearchabibliometricreview AT wenwenli artificialintelligenceinenergyeconomicsresearchabibliometricreview |