A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students

This paper examines the social, organisational and individual factors that may affect students’ acceptance of e-learning systems in higher education in a cross-cultural context. A questionnaire was developed based on an extended technology acceptance model (TAM). A total sample of 1173 university students from two private universities in Lebanon and one university in England participated in this study. After performing the satisfactory reliability and validity checks, the hypothesised model was estimated using structural equation modeling. The findings of this study revealed that perceived usefulness (PU), perceived ease of use (PEOU), social norms (SNs), perceived quality of work life (QWL), computer self-efficacy (SE) and facilitating conditions (FC) are significant determinants of behavioural intentions (BIs) and usage of e-learning system for the Lebanese and British students. QWL, the newly added variable, was found the most important construct in explaining the causal process in the model for both samples. Differences were found between Lebanese and British students with regard to PEOU, SN, QWL, FC, SE and actual usage; however, no differences were detected in terms of PU and BI. Overall, the proposed model achieves acceptable fit and explains for 69% of the British sample and 57% of the Lebanese sample of its variance which is higher than that of the original TAM. Our findings suggest that individual, social and organisational factors are important to consider in explaining students’ BI and usage of e-learning environments. Introduction The usage of e-learning, also known as web-based learning system, has been growing steadily during the last two decades. This growth is due to the increased competition among high educational institutions in order to attract students and meet their educational needs and goals (Clark & Mayer, 2011) and to support both face-to-face and remote course delivery without the constraints of time and distance (Park, 2009). A web-based learning system is considered to be successful if it can replicate classroom experience and consider the students’ needs British Journal of Educational Technology Vol 46 No 4 2015 739–755 doi:10.1111/bjet.12169 © 2015 The Authors. British Journal of Educational Technology published by John Wiley & Sons Ltd on behalf of BERA. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. Practitioner Notes What is already known about the topic • The generalisability and validity of technology acceptance model (TAM) is still questionable in terms of holding across cultures, particularly in non-western contexts. • Various theoretical models, including TAM, have been widely used to explain users’ behavioural intention (BI) and usage of technology. • The acceptance and adoption of technology by students can be influenced by their cultural background. • Student perception towards e-learning is important. What this paper adds • A cohesive investigation of the key factors that contribute to the acceptance of e-learning. • Extends TAM to include social, organisational and individual factors and investigates whether those factors better help explaining and predicting the students’ BI and usage of e-learning systems. • Cross-cultural validation of TAM in an e-learning context to enhance its generalisability. • Provides empirical evidence on the role of quality of work life (QWL), the newly added variable in the e-learning context, which was found the strongest predictor affecting the BI; this highlights the importance of including such factors in future research. • Validation results confirm that British and Lebanese students are different in terms of perceived ease of use, social norms, QWL, facilitating conditions, computer selfefficacy and actual usage; however, no differences were detected in terms of PU and BI. Implications for practice and/or policy • Policy makers should consider the important role that individual, social and organisational factors play in explaining students’ BI and usage of e-learning environments. • Higher educational institutions should keep investing in technology and focus on decreasing obstacles related to adoption and implementation of technology integration in order to improve their students’ learning experience. • In cross-cultural settings, students’ adoption and acceptance of e-learning may depend on their cultural background. • In terms of subjective norm, it is necessary for instructors to put more emphasis on e-learning by announcing to the students that using the system is mandatory, and it is also advised that practitioners should persuade users who are familiar with the system to help promote it to other users by offering a greater variety of e-learning courses and advertising the benefits of e-learning to attract students. • Policy makers should provide all facilities for the students to use the system including the necessary hardware and software. They should also emphasise on the importance of such technologies on enhancing the students’ QWL. • Both onand off-line support in addition to training are necessary to increase e-learning self-efficacy. Additionally, providing a system which promotes ease of use and more user-friendliness could play a key role in enhancing learning effectiveness and efficiency. 740 British Journal of Educational Technology Vol 46 No 4 2015 © 2015 The Authors. British Journal of Educational Technology published by John Wiley & Sons Ltd on behalf of BERA. (Sanchez-Franco, 2010). If the students refuse to use the system, then its benefits will not be fully utilised (Tarhini, Hone & Liu, 2013b). Additionally, although the internet may be considered as a global technology, the efficiency of such tools should also be measured locally as users usually work in local/national contexts (Li & Kirkup, 2007; Teo, 2011). Therefore, due to this phenomenon of the globalisation of web-based learning systems in education, it has become imperative for practitioners and policy makers to understand the user acceptance of such systems in order to enhance the students’ learning experience (Liaw & Huang, 2011). However, recent studies have shown that web-based learning system implementation is not simply a technological solution but also a process of many different factors, such as social factors (Tarhini, Hone & Liu, 2013c; Teo, 2010), organisational such as facilitating conditions (FCs) (Sun & Zhang, 2006) and individual factors such as computer efficacy (Liaw, 2008) in addition to behavioural and cultural factors. Such major factors play an important role in how the system is developed and used (Teo, Luan & Sing, 2008; Zhang, Zhao & Tan, 2008). The need to understand the acceptance and adoption of technology by students in the context in developing and developed countries highlights the importance of investigating the factors that influence the students’ acceptance of technology. Various theoretical models have been developed (the theory of reasoned action, the theory of planned behaviour, innovation diffusion theory, unified theory of acceptance and use technology, the technology acceptance model [TAM]) to investigate and explore the determinants of user’s behaviour towards adoption and using information technology. This study employs the TAM (Davis, 1989) due to its acceptable explanatory power and popularity in a number of application areas (Venkatesh & Bala, 2008). Since it has been developed, TAM has been extensively used, tested and extended to explain technology adoption and success in a number of application areas (eg, Bagozzi, 2007; Yousafzai, Foxall & Pallister, 2007) and in e-learning context (eg, Park, 2009; Sánchez & Hueros, 2010; Teo, 2009b, 2011; Zhang et al, 2008). Although the TAM measures and predicts the acceptance and usage level of technology, there have been some criticisms concerning the theoretical contributions of the model, specifically its ability to fully explain technology adoption and usage (eg, Bagozzi, 2007; Benbasat & Barki, 2007; Straub & Burton-Jones, 2007). Consequently, the existing parameters of the TAM neglected investigating other essential predictors and factors that may affect the adoption and acceptance of technology, such as social, organisational and individual factors. Additionally, in a cross-cultural context, TAM has been criticised for showing bias (McCoy, Everard & Jones, 2005; Straub, Keil & Brenner, 1997). For example, Straub et al (1997) applied TAM in Japan, USA and Switzerland. They found that TAM produced similar results between the USA and Switzerland, but different results were noticed between the USA and Japan. Furthermore, many TAM studies focus on western/developed countries, while TAM has not been widely tested within nonwestern/developing countries (Teo et al, 2008). Consequently, Teo et al (2008) emphasise on the importance of testing the TAM in different cultures as it is argued that when Davis developed the TAM (Davis, 1989), he did not take into consideration the unbiased reliability of TAM in crosscultural settings. Additionally, the applicability of TAM is limited in the educational settings as much of the research has been carried out in non-educational contexts. Faced with these limitations, this study aims to add new variables, namely social norms (SNs), quality of work Life (QWL), computer self-efficacy (SE) and FCs, to the proposed research model to investigate the extent to which these variables affect students’ willingness to adopt and use web-based learning systems and investigate whether there are differences among these factors between developing and developed world, specifically Lebanon as developing world and England as developed world, in addition to Blackboard as a web-based learning system. Blackboard is considered one of the most popular web-based learning system tools in higher education today as e-Learning acceptance in UK and Lebanon 741 © 2015 The Authors. British Journal of Educational Technology published by John Wiley & Sons Ltd on behalf of BERA. it provides a framework for course delivery in addition to its ease of use by learners (Carvalho, Areal & Silva, 2011). According to Blackboard Inc. (2012), it is defined as “the comprehensive technology platform for teaching and learning, community building, content management and sharing, and measuring learning outcomes and consists of integrated modules, with a core set of capabilities that work together.” It integrates communication tools, including a bulletin board, chat room and private e-mail. In addition graphics, video and audio files can be included into a Blackboard site. Blackboard also provides instructional tools to support course content such as a glossary, references, self-test and quiz module. Students, too, can place assignments and other materials in Blackboard for courses in which they are enrolled. Furthermore, Blackboard also gives academic staff course management tools for grading, tracking student interaction and monitoring class progress (Iskander, 2008). Such features can facilitate interaction between academic staff and students (Iskander, 2008). Extending the TAM model to include social, organisational and individual factors in two cultures allows us to explore the generalisability and applicability of the proposed model in the context of web-based learning system in two cultures and also allows exploration of where differences may lie between the cultures involved. This will also help policy makers and practitioners to gain a deeper understanding of the students’ acceptance of web-based learning systems. As shown in Table 1, England and Lebanon were chosen for this study because they represent nearly reverse positions on all cultural dimensions presented by Hofstede and Hofstede (2005). England is high on individualism and masculinity but low in power distance and uncertainty avoidance. On the other hand, Lebanon is low on individualism, moderate on masculinity, and high on power distance and uncertainty avoidance. In addition, compared with England, Lebanon remains relatively unexplored in terms of technology acceptance, and the investment in technology in the educational system is still immature compared with western countries as universities and higher education institutions support traditional styles of pedagogy in education due to the lack of financial resources or trained staff (Baroud & Abouchedid, 2010; Nasser & Abouchedid, 2000; UNDP, 2002) which in turn may affect the acceptance of technology within such countries. These differences also demonstrate the importance of understanding the role of cross-cultural studies. Additionally, the limitations that emerge from TAM especially on holding equally well across cultures and the inconsistency in previous studies’ results (Gefen & Straub, 1997; McCoy, Galletta & King, 2005; Srite & Karahanna, 2006; Teo et al, 2008) direct our research to a cross-cultural comparison between those two countries. The paper is structured as follows. The second section presents and explains our research model and describes the research hypotheses in detail. This is followed by the research method that guided the research in the third section. The fourth section presents the results of the proposed model. Finally, the fifth section discusses the main findings of the study and concludes the paper. Theoretical framework This paper highlights previous literature that used TAM in an educational context and proposes an e-learning conceptual model based on extended TAM. The model includes SN, QWL, SE and FC Table 1: Cultural differences between England and Lebanon on Hofstede’s cultural dimensions Country Power distance Masculinity Individualism Uncertainty avoidance Lebanon (Arab countries) 80 53 38 68 England 35 66 89 35 Values adopted from Hofstede & Hofstede, 2005. 742 British Journal of Educational Technology Vol 46 No 4 2015 © 2015 The Authors. British Journal of Educational Technology published by John Wiley & Sons Ltd on behalf of BERA. as additional predictor variables within the extended TAM. Figure 1 presents the overall conceptual model, and the sections that follow illustrate and explain all of the predicted relationships of the previous literature studies.