scholarly journals The Impacts of Cloud Computing Adoption at Higher Education Institutions: A SWOT Analysis

2015 ◽  
Vol 127 (4) ◽  
pp. 15-21 ◽  
Author(s):  
Mahmoud Odeh ◽  
Kevin Warwick ◽  
Alexeis Garcia-Perez
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Swot Analysis ◽  
Higher Education Institutions ◽  
Cloud Computing Adoption

scholarly journals Cloud Computing Adoption in Higher Education Institutions: A Systematic Review

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 63722-63744 ◽  
Author(s):  
Yousef A. M. Qasem ◽  
Rusli Abdullah ◽  
Yusmadi Yah Jusoh ◽  
Rodziah Atan ◽  
Shahla Asadi
Keyword(s):  
Higher Education ◽  
Systematic Review ◽  
Cloud Computing ◽  
Higher Education Institutions ◽  
Cloud Computing Adoption

scholarly journals A Multi-Analytical Approach to Predict the Determinants of Cloud Computing Adoption in Higher Education Institutions

2020 ◽  
Vol 10 (14) ◽  
pp. 4905 ◽  
Author(s):  
Yousef A. M. Qasem ◽  
Shahla Asadi ◽  
Rusli Abdullah ◽  
Yusmadi Yah ◽  
Rodziah Atan ◽  
...  
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Structural Equation ◽  
Higher Education Institutions ◽  
Sem Analysis ◽  
Decision Makers ◽  
Equation Modeling ◽  
Managerial Decision ◽  
Cloud Computing Adoption ◽  
Analytical Approaches

Cloud computing (CC) delivers services for organizations, particularly for higher education institutions (HEIs) anywhere and anytime, based on scalability and pay-per-use approach. Examining the factors influencing the decision-makers’ intention towards adopting CC plays an essential role in HEIs. Therefore, this study aimed to understand and predict the key determinants that drive managerial decision-makers’ perspectives for adopting this technology. The data were gathered from 134 institutional managers, involved in the decision making of the institutions. This study applied two analytical approaches, namely variance-based structural equation modeling (i.e., PLS-SEM) and artificial neural network (ANN). First, the PLS-SEM approach has been used for analyzing the proposed model and extracting the significant relationships among the identified factors. The obtained result from PLS-SEM analysis revealed that seven factors were identified as significant in influencing decision-makers’ intention towards adopting CC. Second, the normalized importance among those seven significant predictors was ranked utilizing the ANN. The results of the ANN approach showed that technology readiness is the most important predictor for CC adoption, followed by security and competitive pressure. Finally, this study presented a new and innovative approach for comprehending CC adoption, and the results can be used by decision-makers to develop strategies for adopting CC services in their institutions.

scholarly journals Cloud Computing Adoption among Higher Education Institutions in Yemen: An Integrated Conceptual Framework

2018 ◽  
Vol 7 (4.36) ◽  
pp. 429
Author(s):  
Abdulnoor Saleh ◽  
Sulfeeza Mohd Drus ◽  
Siti Salbiah M. Shariff
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Conceptual Framework ◽  
Technology Acceptance ◽  
New Technologies ◽  
Higher Education Institutions ◽  
Middle Eastern ◽  
Structured Interview ◽  
Teaching Staff ◽  
Cloud Computing Adoption

Researches in technology adoption among the Middle Eastern countries are more concentrated on e-government, e-commerce, and internet banking domains. Higher education institutions (HEIs) in these countries fall behind their Western counterparts due to the cutting edge technology adopted for research, teaching, and collaboration in the Western countries. One of the Middle Eastern countries, which is the focus of this research, Yemen, still adopt the conventional way of teaching in the HEIs, which could result in failures to accomplish the optimal desired educational performance. Higher education sector in Yemen faces a number of obstacles and challenges in delivering a good education to its entire population in terms of lack of reliable infrastructure; limited financial resources; lack of teaching staff and expertise; and lack of IT personnel to manage the existing restricted IT infrastructure. Cloud computing, a pool of computer-related resources and services, is seen as one of new technologies which can assist in improving educational delivery in Yemen. Thus, this study firstly, identified the factors that influence the cloud computing adoption in general. Then, it categorized these factors into four (4) domains, namely technological, organizational, environmental and individual domains; and lastly, validated the selected factors using semi-structured interview with IT experts. Based on the validation session with the IT experts, the factors were ranked based on their applicability and suitability in Yemeni’s higher education environments and 13 factors were selected. These 13 factors are adopted from Technology Acceptance Model (TAM), Theory of Reasoned Action (TRA), Technology-Organization-Environment (TOE) framework and Diffusion of Innovation (DOI) theory. Then, a conceptual framework was developed using these 13 factors to identify the significant factors that influence cloud computing adoption in HEIs in Yemen. It is hoped by having a better understanding on the factors that influence cloud computing adoption in HEIs in Yemen, the responsible parties such as the government agencies, HEIs managements and staff will be more prepared to ensure successful adoption of cloud computing in their HEIs and ultimately help Yemen to improve its higher education delivery to its people.  

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