| Issue |
E3S Web Conf.
Volume 680, 2025
The 4th International Conference on Energy and Green Computing (ICEGC’2025)
|
|
|---|---|---|
| Article Number | 00084 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/e3sconf/202568000084 | |
| Published online | 19 December 2025 | |
A bibliometric analysis: Exploring the intersection of IA and decarbonisation
Laboratory of Modeling and Simulation of Intelligent Industrial Systems, ENSET MOHAMMEDIA, Hassan II University, Morocco
* Corresponding author: youssra.zegraoui.1998@gmail.com
The integration of Artificial Intelligence (AI) and Industry 4.0 technologies into decarbonisation strategies has attracted increasing scholarly attention. To capture the dynamics of this emerging field, a bibliometric analysis was conducted using the Scopus database for the period 2014–2024. After data cleaning, a corpus of about 700 documents was analysed through descriptive statistics and network visualisation with VOSviewer.The results show a sharp increase in publications after 2018, with a peak in 2024, confirming the growing centrality of AI and Industry 4.0 in sustainable industrial transitions. Geographically, the United Kingdom, India, China, and Italy emerge as leading contributors, while countries such as Morocco remain peripheral but show growing participation. In terms of document types, journal articles (56.5%) dominate over conference papers (43.5%), with Sustainability (Switzerland) and the Journal of Cleaner Production among the most prolific outlets. Collaboration networks reveal a concentration of influential scholars in sustainable supply chain and digital transformation research. Keyword co-occurrence mapping highlights major clusters around artificial intelligence, Industry 4.0, machine learning, sustainability, and digitalisation, complemented by emerging themes such as circular economy and energy efficiency. This study provides an updated overview of the field, offering insights into research trends, collaboration patterns, and thematic evolution to guide future investigations.
Key words: Artificial Intelligence / Industry 4.0 / Decarbonisation / Bibliometric Analysis
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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