The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Artificial intelligence in E-Commerce: a bibliometric study and literature review
Open accessAbstract
This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes guidelines on how information systems (IS) research could contribute to this research stream. To this end, the innovative approach of combining bibliometric analysis with an extensive literature review was used. Bibliometric data from 4335 documents were analysed, and 229 articles published in leading IS journals were reviewed. The bibliometric analysis revealed that research on AI in e-commerce focuses primarily on recommender systems. Sentiment analysis, trust, personalisation, and optimisation were identified as the core research themes. It also places China-based institutions as leaders in this researcher area. Also, most research papers on AI in e-commerce were published in computer science, AI, business, and management outlets. The literature review reveals the main research topics, styles and themes that have been of interest to IS scholars. Proposals for future research are made based on these findings. This paper presents the first study that attempts to synthesise research on AI in e-commerce. For researchers, it contributes ideas to the way forward in this research area. To practitioners, it provides an organised source of information on how AI can support their e-commerce endeavours.
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Citations
Cites
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Cited by
Weber, P., Carl, K. V., & Hinz, O. (2024) · Management Review Quarterly · doi:10.1007/s11301-023-00320-0 · Cited by 292
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Metadata
- Authors
- Bawack, R. E., Wamba, S. F., Carillo, K. D. A., & Akter, S.
- Venue
- Electronic Markets
- Published
- 2022-03
- Volume
- 32
- Issue
- 1
- Pages
- 297-338
- ISSN
- 1019-6781 (ISSN-L)
- 1422-8890
- OpenAlex
- W4220923293
- Cited by
- 372
- References
- 28
- FWCI
- 24.15
- Type
- journal article
- Language
- en
- Open access
- bronze
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
