A bibliometric analysis insights into the intellectual dynamics of artificial intelligence for the micro, small, and medium enterprises
This study addressed the gaps in existing research on how artificial intelligence (AI) can be used by micro, small, and medium enterprises (MSMEs) by providing a comprehensive overview of the field’s intellectual structure. A systematic literature review was applied following the “preferred reportin...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Cogent Business & Management |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23311975.2025.2491684 |
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| Summary: | This study addressed the gaps in existing research on how artificial intelligence (AI) can be used by micro, small, and medium enterprises (MSMEs) by providing a comprehensive overview of the field’s intellectual structure. A systematic literature review was applied following the “preferred reporting items for systematic reviews and meta-analyses” methodology and bibliometric analysis with VOSviewer software to analyze 124 publications from the Scopus database published between 1 January 2014 and 15 June 2024. Our findings indicated that publications and citations have proliferated, led by the UK, India, and the US. Key research themes included AI applications in e-commerce, manufacturing, digital transformation, and sustainability for MSMEs. The foundation literature centered on AI adoption models, performance measurement systems, and sustainability frameworks. Methodological approaches favored quantitative surveys and case studies, with an increasing trend toward mixed methods. Future research avenues were identified including integrated theoretical frameworks, longitudinal studies, cross-cultural comparisons, and exploring AI’s ethical implications. This study’s novelty lies in its comprehensive mapping of AI for the MSME research landscape. Our findings provide valuable guidance for researchers, MSME managers, and policymakers navigating the complex terrain of AI adoption. |
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| ISSN: | 2331-1975 |