@article{article_641961, title={THE INFLUENCE OF PERCEIVED USEFULNESS, SOCIAL INFLUENCE, INTERNET SELF-EFFICACY AND COMPATIBILITY ON USERS’ INTENTIONS TO ADOPT E-LEARNING: INVESTIGATING THE MODERATING EFFECTS OF CULTURE}, journal={IJAEDU- International E-Journal of Advances in Education}, volume={5}, pages={300–320}, year={2020}, DOI={10.18768/ijaedu.593878}, author={S Faqih, Khaled M}, keywords={adoption,e-learning,culture,WarpPLS,Jordan}, abstract={<p class="MsoNormal"> <span lang="en-us" xml:lang="en-us">The current
study has been inspired by two significant issues: (1) The proliferation of e- </span> <span lang="en-us" xml:lang="en-us">technologies such as
e-learning have dramatically <span>motivated global
research intended to </span> advance our knowledge of the dynamics of these
technologies in varying environmental contexts and settings, and (2) the
importance of cultural values at individual-level analysis in technology
adoption merits greater level of attention and interests from researchers and
practitioners, particularly in relation to developing country contexts. This
study intends to investigate the significance of highly influential adoption
factors acknowledged as relevant in prior literature in predicting user </span> <span lang="en-us" xml:lang="en-us">’s
behavioral intention to adopt new technologies. These <span>potentially important </span>factors were drawn from highly popular
technology adoption and social theories including perceived usefulness
(Technology Acceptance Model), social influence <span>
(Theory <span class="apple-converted-space">  </span>of Planned Behavior <span class="apple-converted-space">), </span> </span>Internet self-efficacy ( <span>Social </span>Cognitive <span>Theory)
and </span> perceived compatibility <span> (Innovation
Diffusion Theory) <span class="apple-converted-space">. </span> </span>Further, the
present study <span>examines the moderating impact of
both </span> </span> <span lang="en-us" xml:lang="en-us">individualism-collectivism and uncertainty
avoidance cultural dimensions at individual-level </span> <span lang="en-us" xml:lang="en-us"> </span> <span lang="en-us" xml:lang="en-us">on the hypothesized relationships linking these </span> <span lang="en-us" xml:lang="en-us">highly influential adoption </span> <span lang="en-us" xml:lang="en-us">factors with behavioral intention to adopt e-learning environment in
order to </span> <span lang="en-us" xml:lang="en-us">facilitate and enhance learning processes and in an effort to
achieve </span> <span lang="en-us" xml:lang="en-us">value maximization </span> <span lang="en-us" xml:lang="en-us">and waste minimization  <span>requirements in the context of e-learning technology. </span>The
empirical data which consists of 262 valid datasets was collected from
undergraduate university students in Jordan via self-administered paper-based <span class="apple-converted-space"> <span>questionnaire </span> </span>.
The questionnaire was developed from previously accepted and validated a set of
measurements items. The empirical data was numerically assessed and analyzed
with the help of WarpPLS 5.0. The findings of this study demonstrate that
perceived usefulness, social influence <span>, </span>
Internet self-efficacy <span>and </span> perceived
compatibility are important predictors of individuals </span> <span lang="en-us" xml:lang="en-us">’ behavioral
intention to adopt e-learning technology. Further, the current findings provide
adequate empirical evidence to support all hypotheses involving moderating
effects with one exception whereby both </span> <span lang="en-us" xml:lang="en-us">individualism-collectivism
and uncertainty avoidance </span> <span lang="en-us" xml:lang="en-us"> cultural values have little statistical significance on the
relationship linking perceived usefulness with behavioral intention to adopt
e-learning technologies. Interestingly, <span>the <span class="apple-converted-space">  </span>proposed model <span class="apple-converted-space">  </span>explains <span class="apple-converted-space">  </span>a substantial amount of variance (63%)
which signifies that the model fits the data well. </span>Research findings are
discussed and contribution to theory and practice are presented. </span> </p>}, number={15}, publisher={OCERINT International Organization Center of Academic Research}