Investigating users’ perspectives on e-learning: An integration of TAM and IS success model Hossein Mohammadi ⇑ Department of Public Administration, Allameh Tabataba’i University, Tehran, Iran article info Article history: Available online 12 January 2015 Keywords: E-learning Quality Satisfaction Intention to use Actual use abstract The purpose of this paper is to examine an integrated model of TAM and D&M to explore the effects of quality features, perceived ease of use, perceived usefulness on users’ intentions and satisfaction, along- side the mediating effect of usability towards use of e-learning in Iran. Based on the e-learning user data collected through a survey, structural equations modeling (SEM) and path analysis were employed to test the research model. The results revealed that ‘‘intention’’ and ‘‘user satisfaction’’ both had positive effects on actual use of e-learning. ‘‘System quality’’ and ‘‘information quality’’ were found to be the primary factors driving users’ intentions and satisfaction towards use of e-learning. At last, ‘‘perceived usefulness’’ mediated the relationship between ease of use and users’ intentions. The sample consisted of e-learning users of four public universities in Iran. Past studies have seldom examined an integrated model in the context of e-learning in developing countries. Moreover, this paper tries to provide a literature review of recent published studies in the field of e-learning. Ó 2014 Elsevier Ltd. All rights reserved. 1. Introduction To meet educational purposes and students’ demands, e-learn- ing development emerges to be a catalyst for today educational institutions (Alsabswy, Cater-Steel, & Soar, 2013; Docimini & Palumbo, 2013). E-learning can be defined as a dynamic and imme- diate learning environment through the use of internet to improve the quality of learning by providing students with access to resources and services, together with distant exchange and collaboration (Docimini & Palumbo, 2013; Jeong & Hong, 2013). E-learning supports learners with some special capabilities such as interactivity, strong search, immediacy, physical mobility and situating of educational activities, self-organized and self-directed learning, corporate training, personalized learning, and effective technique of delivering lesson and gaining knowledge (Bidin & Ziden, 2013; Docimini & Palumbo, 2013; Jeong & Hong, 2013; Martin & Ertzberger, 2013; Viberg & Gronlung, 2013). E-learning has a positive impact on both teachers and students in that it pos- itively affects the duration of their attention, learning and training tenacity, and their attitudes towards collaboration and interaction (Chen & Tseng, 2012; Ozdamli & Uzunboylu, 2014). Past studies have indicated that anywhere and anytime learning and access to information and communication are facilitated through using e-learning (Chen & Tseng, 2012; Ho & Dzeng, 2010; Islam, 2013; Pena-Ayala, Sossa, & Mendez, 2014). Kratochvíl (2013) and Abachi and Muhammad (2013) note that all individuals involved in e-learning are fond of using it towards learning because of flex- ible access in terms of time, space, and pace and online collabora- tive learning. However, demand for the development of e-learning is increasingly growing; still the need for research on potential fac- tors affecting e-learning adoption like quality which is the heart of education and training in all countries (Ehlers & Hilera, 2012), is felt especially in the context of developing countries (Masoumi & Lindstrom, 2012), a fact that warrants investigation into it. Past studies have used information technology adoption theories such as Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT) and the Unified Theory of Acceptance and Use of Technology (UTAUT) and the DeLone & McLean’s model to explore e-learning users’ behavioral patterns. Some of these stud- ies have taken the barriers and the drivers of e-learning adoption into consideration (e.g., Chen & Tseng, 2012; Islam, 2012, 2013, 2014; Sumak, Hericko, & Punik, 2011). In this paper it is attempted to introduce an integrated model of TAM and DeLone & McLean’s model for predicting individual’s actual use of e-learning system in Iran. As Li, Duan, Fu, and Alford (2012) note, it is essential to examine the relationship between e-learners’ experiences, percep- tions, and their behavioral intentions to use, because system use is an important indicator of the system’s success. http://dx.doi.org/10.1016/j.chb.2014.07.044 0747-5632/Ó 2014 Elsevier Ltd. All rights reserved. ⇑ Address: Pars Pamchal Alley, block 17, No 2, Naghshe Iran St. Ansar Alhossein St. Second Square, Kosar, Qazvin, Iran. Tel.: +98 9192864512, +98 9214563704. E-mail addresses: H.mohammadi901@st.atu.ac.ir, Hossein662@gmail.com Computers in Human Behavior 45 (2015) 359–374 Contents lists available at ScienceDirect Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh