AI IN E-COMMERCE: A BIBLIOMETRIC REVIEW OF TRENDS, THEMES, AND EMERGING RESEARCH DIRECTIONS
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Dr Richa Kalpesh Saxena
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B.Sc. Finance, NMIMS, Anil Surendra Modi School of Commerce, Mumbai Campus, India
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Abstract
This bibliometric analysis aims to trace the trends in development, research themes and knowledge gaps in AI in e-commerce using a bibliometric methodology. In total, 483 articles were gathered from the database ScienceDirect, using the Systematic Literature Review (SLR) with PRISMA guidelines, and analysed using Biblioshiny and VOSviewer. The results have indicated that the studies in question remained scarce and fragmented until approximately 2017 and experienced a considerable increase after that time, surpassing 100 publications per annum in 2025. Procedia Computer Science and multiple business and retail-oriented publications proved to be among the sources that had the highest impact, confirming the interdisciplinary nature of the topic. Artificial intelligence, e-commerce and machine learning proved to be the most frequently used keywords, whereas the digital transformation, supply chain and SMEs proved to be the themes that had already been well-developed in comparison to such niche themes as chatbots and accessibility. As seen from the literature review, artificial intelligence has been utilized across almost all facets of e-commerce, from logistics to consumer experience, personalization, and fraud detection, although the literature review is limited in terms of the geographical area covered and also in that it fails to take into consideration the differential impact that AI has on different segments of consumers. As a result of this literature review, this study suggests a future research agenda encompassing topics such as generative AI, responsible AI, and cross-cultural adoption
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Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 10
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Oct 12 2026
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Mehta, S., Markande, S., Gada, T. & Aggarwal, V. (2026). AI in E-Commerce: A Bibliometric Review of Trends, Themes, and Emerging Research Directions. International Journal of Science, Strategic Management and Technology, 02(10), 1-9. https://doi.org/10.55041/ijsmt.v2i10.059
Mehta, Soham, et al.. "AI in E-Commerce: A Bibliometric Review of Trends, Themes, and Emerging Research Directions." International Journal of Science, Strategic Management and Technology, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i10.059.
Mehta, Soham,Swara Markande,Tanish Gada, and Vaani Aggarwal. "AI in E-Commerce: A Bibliometric Review of Trends, Themes, and Emerging Research Directions." International Journal of Science, Strategic Management and Technology 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i10.059.
References
Fan, Z. et al. (2024). Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process. arXiv. https://arxiv.org/abs/2401.03244
Jiang, W. (2023). Enhancing Operational Efficiency in E-Commerce Through Artificial Intelligence and Information Management Integration. Revue d'Intelligence Artificielle, 37(6). https://ieta.org/journals/ria/paper/10.18280/ria.370619
Peruchini, M., Modena da Silva, G., & Monteiro Teixeira, J. (2024). Between artificial intelligence and customer experience: a literature review on the intersection. Discover Artificial Intelligence, 4(1). https://link.springer.com/article/10.1007/s44163-024-00105-8
Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. T. (2024). E-commerce and consumer behavior: A review of AI-powered personalization and market trends. https://gscarr.gsconlinepress.com/content/e-commerce-and-consumer-behavior-review-ai-powered-personalization-and-market-trends
Aljarboa, S. (2024). Factors influencing the adoption of artificial intelligence in e-commerce by small and medium-sized enterprises. International Journal of Information Management Data Insights, 4(2), 100279. https://doi.org/10.1016/j.ijimei.2024.100279
Mamdouh, H. (2024). Are young adult consumers ready to be intelligent shoppers? The importance of perceived trust and the usefulness of AI-powered retail platforms in shaping purchase intention. Young Consumers, 25(6), 969–989. https://doi.org/10.1108/YC-02-2024-1991
Chaudhary, A., & Jain, K. (n.d.). Voice-Assisted E-Commerce: Enhancing Accessibility for Visually Impaired Users Using Generative AI. In Generative Artificial Intelligence. https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifi erValue=10.1201/9781003565703-12&type=chapterpdf
Giang, N. T. P., Tan, T. D., & Nhung, L. T. H. (2025). Determinants of E-commerce adoption and its effect on marketing performance among Vietnamese SMEs: A PLS-SEM approach using the TOE framework. Journal of Open Innovation: Technology, Market, and Complexity, 11(4). https://doi.org/10.1016/j.joitmc.2025.100670
Hurtado, P. A., Dorneles, C., & Frazzon, E. (2019). Big Data application for E-commerce's Logistics: A research assessment and conceptual model. IFAC-PapersOnLine, 52(13), 838–843. https://doi.org/10.1016/j.ifacol.2019.11.234
Luo, S. (2026). Cybersecurity in E-commerce supply chain operations. In Encyclopedia in Operations Management (pp. Vol1:459–Vol1:467). Elsevier. https://doi.org/10.1016/B978-0-443-28993-4.00017-2
Jiang, W. (2023). Enhancing Operational Efficiency in E-Commerce Through Artificial Intelligence and Information Management Integration. Revue d'Intelligence Artificielle, 37(6). https://ieta.org/journals/ria/paper/10.18280/ria.370619
Peruchini, M., Modena da Silva, G., & Monteiro Teixeira, J. (2024). Between artificial intelligence and customer experience: a literature review on the intersection. Discover Artificial Intelligence, 4(1). https://link.springer.com/article/10.1007/s44163-024-00105-8
Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. T. (2024). E-commerce and consumer behavior: A review of AI-powered personalization and market trends. https://gscarr.gsconlinepress.com/content/e-commerce-and-consumer-behavior-review-ai-powered-personalization-and-market-trends
Aljarboa, S. (2024). Factors influencing the adoption of artificial intelligence in e-commerce by small and medium-sized enterprises. International Journal of Information Management Data Insights, 4(2), 100279. https://doi.org/10.1016/j.ijimei.2024.100279
Mamdouh, H. (2024). Are young adult consumers ready to be intelligent shoppers? The importance of perceived trust and the usefulness of AI-powered retail platforms in shaping purchase intention. Young Consumers, 25(6), 969–989. https://doi.org/10.1108/YC-02-2024-1991
Chaudhary, A., & Jain, K. (n.d.). Voice-Assisted E-Commerce: Enhancing Accessibility for Visually Impaired Users Using Generative AI. In Generative Artificial Intelligence. https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifi erValue=10.1201/9781003565703-12&type=chapterpdf
Giang, N. T. P., Tan, T. D., & Nhung, L. T. H. (2025). Determinants of E-commerce adoption and its effect on marketing performance among Vietnamese SMEs: A PLS-SEM approach using the TOE framework. Journal of Open Innovation: Technology, Market, and Complexity, 11(4). https://doi.org/10.1016/j.joitmc.2025.100670
Hurtado, P. A., Dorneles, C., & Frazzon, E. (2019). Big Data application for E-commerce's Logistics: A research assessment and conceptual model. IFAC-PapersOnLine, 52(13), 838–843. https://doi.org/10.1016/j.ifacol.2019.11.234
Luo, S. (2026). Cybersecurity in E-commerce supply chain operations. In Encyclopedia in Operations Management (pp. Vol1:459–Vol1:467). Elsevier. https://doi.org/10.1016/B978-0-443-28993-4.00017-2
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