Title: Explaining and predicting continuance usage intention of e-learning recommender systems: an empirical evidence from Saudi Arabia
Authors: Hadeel Alharbi; Kamaljeet Sandhu
Addresses: University of New England, Armidale, NSW, Australia ' University of New England, Armidale, NSW, Australia
Abstract: This paper examines the factors that may influence students' acceptance and the continuance usage intention of e-learning recommender systems in higher education institutions in Saudi Arabia. A questionnaire was developed based on an extended technology acceptance model (TAM). A total sample of 353 university students from various universities in Saudi Arabia participated in this study. The findings of this study revealed that perceived usefulness (PU) and perceived ease of use (PEOU) are significant determinants of e-learning recommenders' system initial acceptance. The results also showed that the service quality, a newly added external construct, has significant impact on perceived recommender system ease of use. User experience of recommender system, the second newly added construct, was found to have a significant effect on perceived recommender system usefulness. Finally we found that students' acceptance of e-learning recommender systems positively and directly influences their continuance usage intention.
Keywords: Saudi Arabia; e-learning; recommender system; technology acceptance model; TAM; adoption.
International Journal of Business Information Systems, 2018 Vol.29 No.3, pp.297 - 323
Received: 04 Nov 2016
Accepted: 15 Jan 2017
Published online: 11 Oct 2018 *