E-Learning through a cloud-based learning management system, with its various added advantageous features, is a widely used pedagogy at educational institutions in general and more particularly during and post Covid-19 period. Successful adoption and implementation of cloud ELearning seems difficult without significant service quality. Aims: This study aims to identify the determinant of cloud E-Learning service quality. Methodology: A theoretical model was proposed to gauge the cloud E-Learning service quality by extensive literature search. The most important factors for cloud E-Learning service quality were screened. Instruments for each factor were defined properly, and its content validity was checked with the help of Group Decision Makers (GDMs). Empirical testing was used to validate the proposed theoretical model, the self-structured closedended questionnaire was used to conduct an online survey. Findings: Internal consistency of the proposed model was checked with reliability and composite reliability and found appropriate α ≥ 0.70 and CR ≥ 0.70. Indicator Reliability was matched with the help of Outer Loading and found deemed fit OL ≥ 0.70. To establish Convergent Validity Average Variance Extracted, Factor Loading and Composite Reliability were used and found deemed suitable with AVE ≥ 0.50. The HTMT and Fornell–Lacker tests were applied to assess discriminant validity and found appropriate (HTMT ≤ 0.85). Finally, the Variance Inflation Factor was used to detect multicollinearity if any and found internal and external VIF &lt; 3. Conclusions: Theoretical model for cloud E-Learning service quality was proposed. Information Quality, Reliability, Perceived ease of use and Social Influence were considered as explanatory variables whereas actual system usage was the dependent variable. Empirical testing on all parameters stated that the proposed model was deemed fit in evaluating cloud E-Learning service quality. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Exploring the determinants of service quality of cloud elearning system for active system usage