Exploring the Climate Change-AI Nexus: A Bibliometric and Scientometric Study

Chițu Florentina (), Mecu Andra-Nicoleta () and Marin Georgiana-Ionela ()
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Chițu Florentina: Bucharest University of Economic Studies, Bucharest, Romania
Mecu Andra-Nicoleta: Bucharest University of Economic Studies, Bucharest, Romania
Marin Georgiana-Ionela: Bucharest University of Economic Studies, Bucharest, Romania

Proceedings of the International Conference on Business Excellence, 2024, vol. 18, issue 1, 1658-1670

Abstract: The intersection between artificial intelligence (AI) and climate change mitigation has received increased attention as a result of pressing global environmental concerns and technological advancements. This paper will cover key scientific literature about the development and implementation of AI in tackling climate change challenge. Methodologically, bibliometric and scientometric analyses, including cooccurrence and co-citation analysis, were employed to systematically examine research trends and patterns. The major research question focuses on tracing the evolution of AI research in relation to climate change, investigating important drivers of interest and identifying influential works and research groups. The data find a considerable increase in AI and climate change papers after 2015, demonstrating a growing appreciation for AI’s potential to provide novel solutions. Implications of this trend include the use of AI technologies for environmental monitoring, prediction, and policy makers. Moreover, interdisciplinary collaborations on AI and climate change between experts from various fields shown the importance of global climate issues. This paper provides a new idea for the study on AI in climate change, highlighting opportunities for further exploration and collaboration.

Keywords: artificial intelligence; climate change; renewable energy; machine learning; bibliometric analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:18:y:2024:i:1:p:1658-1670:n:1021

DOI: 10.2478/picbe-2024-0138

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