Artificial intelligence in E-Commerce: a bibliometric study and literature review
Ransome Epie Bawack (),
Samuel Fosso Wamba (),
Kevin Daniel André Carillo () and
Shahriar Akter ()
Additional contact information
Ransome Epie Bawack: CEREFIGE - Université de Lorraine
Samuel Fosso Wamba: TBS Business School
Kevin Daniel André Carillo: TBS Business School
Shahriar Akter: University of Wollongong
Electronic Markets, 2022, vol. 32, issue 1, No 18, 297-338
Abstract:
Abstract 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.
Keywords: Artificial intelligence; e-commerce; Literature review; Bibliometrics (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (12)
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DOI: 10.1007/s12525-022-00537-z
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