Factors Affecting Cloud Computing Adoption and Continuance Intention of Students in Thailand

2021 ◽  
Author(s):  
Juthamon Sithipolvanichgul ◽  
Charlie Chen ◽  
Judy Land ◽  
Peter Ractham
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Online Education ◽  
Higher Education Institutions ◽  
Developed Countries ◽  
Perceived Usefulness ◽  
Factors Affecting ◽  
Perceived Risks ◽  
Cloud Computing Adoption ◽  
The Impact

An increasing number of higher education institutions have embraced Cloud Computing Services (CCS) to better respond to the issues arising from the COVID-19 pandemic. Cloud computing has helped to ease the process and lower the cost of offering online education and hybrid learning. However, some universities in Thailand face cloud computing adoption challenges because students lack awareness of the benefits and risks of CCS. Therefore, it is vital to identify the critical factors affecting the initial and continuance adoption of CCS by students in less developed countries. This study adopts a trade-off lens to assess the impact of the perceived usefulness and perceived risks regarding students’ attitudes toward the initial and continuing adoption of CCS. Using a survey of CCS from a large public university in Thailand, we found that performance expectation and effort expectation positively affect perceived usefulness, and that authentication risks positively affect perceived risks. We also found that perceived usefulness rather than perceived risks is a deciding factor in adopting CCS. Higher education institutions in Thailand can accelerate the adoption of CCS by improving students’ perceived performance and reducing the perceived risks.

Is E-Learning a Pro-Active Response to, or Reaction to, Changes in Educational Policy and Patterns of Educational Demand?

2014 ◽  
pp. 253-267
Author(s):  
Allan M. Lawrence ◽  
Peter J. Short ◽  
Deborah Millar
Keyword(s):  
Higher Education ◽  
Educational Policy ◽  
Higher Education Institutions ◽  
Developed Countries ◽  
Quality Factors ◽  
Student Work ◽  
Factors Affecting ◽  
Educational Demand ◽  
E Learning ◽  
The Impact

This chapter reviews and investigates the models and acceptability of E-Learning to the emerging students markets for Higher Education Institutions (HEIs) from the More Developed Countries (MDCs) and seeks to evaluate the differing models of delivery from a practical and a socio-economic perspective. The research also investigates the impact of the shifts in population growth and the subsequent impact upon the levels of demand from students in Less Developed Countries (LDCs) for higher education. In addition, the logistical and quality factors affecting E-Learning are evaluated, looking at the aspects of academic rigour, plagiarism, and the methods of managing the originality and authenticity of student work. Similarly, the research looks at the viability of situations where the education provider may never physically meet the students through the exclusive use of VLEs, and the possible credibility issues that this may present to institutional and awarding body reputations.

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 Investigating the Impact of Cloud Computing Vendor on the Adoption of Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ge Zhang ◽  
Lu Liu ◽  
Hao Guo
Keyword(s):  
Cloud Computing ◽  
Cloud Service ◽  
Relevant Research ◽  
Factors Affecting ◽  
Research Perspective ◽  
Cloud Computing Adoption ◽  
Service Capability ◽  
Initial Scale ◽  
Matched Data ◽  
The Impact

Cloud computing offers significant impacts on organization by changing how information systems are developed, deployed, operated, maintained, and paid for. Therefore, the adoption of cloud computing becomes the focus of relevant research; however, previous studies have mostly studied the factors affecting cloud computing adoption from the perspective of adopters, ignoring the influence of the vendors. This study defines cloud service capability and develops scale to measure it from the perspective of cloud computing vendors to empirically examine the impact of the supply-side of cloud computing. The initial scale of cloud service capability is constructed using qualitative research, and the formal scale is obtained after two rounds of pretest. The statistical results of matched data collected from 132 cloud computing vendors and their users show that cloud service capability significantly affects cloud computing adoption. This study shifts the research perspective on cloud adoption to make theoretical contributions and management insights from the perspective of cloud computing vendors.

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.

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