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.
ABSTRACT
PURPOSE: Despite the great potential Health Information Systems (HIS) have in improving the quality of healthcare delivery services, very few studies have been carried out on the adoption of such systems in developing countries. This article is concerned with investigating the adequacy of UTAUT1 in determining factors that influence the adoption of HIS by clinicians in developing countries, based on the case of Cameroon. METHODS: A paper-based questionnaire was distributed to clinicians in 4 out of 7 major public hospitals in Cameroon. A modified UTAUT was tested using structural equation modeling (SEM) method to identify the determinants of clinicians' intention to use HIS. Self-efficacy and cost-effectiveness were determinants used to extend the original UTAUT. RESULTS: 228 out of 286 questionnaires were validated for this study. The original UTAUT performed poorly, explaining 12% of the variance in clinicians' intention to use HIS. Age was the only significant moderating factor, improving the model to 46%. Self-efficacy and cost effectiveness has no direct significant effect on HIS adoption in the context of this study. CONCLUSIONS: The original UTAUT is not adequate in identifying factors that influence the adoption of HIS by clinicians in developing countries. Simplifying the model by using age as the only moderating factor significantly increases the model's ability to predict HIS adoption in this context. Thus, the younger clinicians are more likely and ready to adopt HIS than the older ones. Context-specific should also be used to increase the explanatory power of UTAUT in any given context.
