Research trend on the application of “e-learning adoption theory”: a scientometric study during 2000-2019, based on Web of Science and Scopus

Abstract

Bibliometric study of the research trend on e-learning adoption theory is essential to investigate the existing literature to identify a suitable theory for new research. Objective of this study is to explore the research trend in scientific literature on e-learning adoption theory. Search of Web of Science and SCOPUS were carried out to find papers dealing with the contours of e-learning adoption theory. This study retrieved 84 research papers from Web of Science and 324 from SCOPUS on the “e-learning adoption theory.” USA and Taiwan accounted for the highest number of publications with 39 papers (12.03%) and 19 papers (22.62%) in SCOPUS and Web of Science respectively. Computer Science has the highest number of papers in SCOPUS whilst Education and Educational Research is the top in Web of Science. China Agricultural University and Universiti Teknologi Malaysia have the highest number of publications four and seven in Web of Science and SCOPUS respectively. National Central University and China Agricultural University are the most productive organization as they have received 321 and 69 citations on e-learning adoption theory in Web of Science and SCOPUS respectively. Among the authors, Tarhini Ali of Brunel University, London has published the highest number of papers (five) on e-learning adoption theory in Web of Science and received 124 citations. Despites, Giannakos, M.N. and Pappas, I.O. have published the same quantity of papers (five) in SCOPUS, they have received only 47 and 22 citations respectively. Journal namely Computers and Education have published the highest number of papers in both databases at 13 (16.05%) and 14 (4.32%) received the highest number of citations at 996 (53.04%) and 1487 (39.37%) for those papers in Web of Science and SCOPUS respectively. Among the technology adoption theories, the Decomposed Theory of Planned Behaviour is more suitable to study e-learning behavior of individuals.