Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/16263
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dc.contributor.authorTarhini, A-
dc.contributor.authorHone, K-
dc.contributor.authorLiu, X-
dc.date.accessioned2018-06-04T12:28:44Z-
dc.date.available2014-01-01-
dc.date.available2018-06-04T12:28:44Z-
dc.date.issued2014-
dc.identifier.citationComputers in Human Behavior, 2014, 41 pp. 153 - 163en_US
dc.identifier.issn0747-5632-
dc.identifier.issnhttp://dx.doi.org/10.1016/j.chb.2014.09.020-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/16263-
dc.description.abstractThe main objective of our study is to (1) empirically investigate the factors that affect the acceptance and use of e-learning in Lebanon, and (2) investigate the role of a set of individual differences as moderators (e.g., age, gender, experience, educational level) in an extended Technology Acceptance Model (TAM). A quantitative methodology approach was adopted in this study. To test the hypothesized research model, data was collected from 569 undergraduate and postgraduate students studying in Lebanon via questionnaire. The collected data were analysed using Structural Equation Modeling (SEM) technique based on AMOS methods in conjunction with multi-group analysis. The result revealed that perceived usefulness (PU), perceived ease of use (PEOU), subjective norms (SN) and Quality of Work Life (QWL) positively affect students' behavioural intention (BI). We also found that experience moderates the relationship between PEOU, PU and SN on e-learning use intention, and that age difference moderates the effects of PEOU, SN and QWL on BI. In addition, educational level moderates the effects of PEOU, SN on BI, and gender moderates the effects of PU, SN and QWL on BI. Contrary to expectations, a moderating role of age on the relationship between PU and BI was not found. Similarly, gender was not found to affect the relationship between PEOU and BI, and educational level did not moderate the relationship between PU or QWL and BI. In light of these findings, implications to both theory and practice are discussed.en_US
dc.format.extent153 - 163-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectIndividual differencesen_US
dc.subjectTechnology acceptanceen_US
dc.subjectTAMen_US
dc.subjecte-learningen_US
dc.subjectStructural equation modelingen_US
dc.subjectDeveloping countriesen_US
dc.titleThe effects of individual differences on e-learning users' behaviour in developing countries: A structural equation modelen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.chb.2014.09.020-
dc.relation.isPartOfComputers in Human Behavior-
pubs.publication-statusPublished-
pubs.volume41-
Appears in Collections:Dept of Computer Science Research Papers

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