Cloud computing (CC) is a recently developed computing paradigm that can be utilized to deliver everything-as-a-service to various businesses. In higher education institutions (HEIs), CC is rapidly being deployed and becoming an integral part of institution experience. CC adoption in HEIs is accompanied by numerous scientific contributions that address the topic from different perspectives. A systematic review of these heterogeneous contributions, which provide a coherent taxonomy, can be considered interesting for HEIs to identify opportunities to use CC in its own context. Therefore, this systematic literature review aims to analyze existing research on adopting and using CC in HEIs, review background research to develop a coherent taxonomy and provide a landscape for future research on CC in HEIs. The outcomes of this paper include a coherent taxonomy and an overview of the basic characteristics of this emerging field in terms of motivation and barriers of adopting CC in HEIs, existing individual and organizational theoretical models to understand the future requirements for extensively adopting and using CC in HEIs, and factors that influence the adoption of CC in HEIs at individual and organizational levels. Considerable information is available in relation to adopting and using CC in HEIs. This review will enhance this information by offering an in-depth analysis of the existing data to bridge any gap and expand on existing literature.

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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.

Resource optimization is a key concern for Higher Education Institutions (HEIs). Cloud Computing, as the recent generation in computing technology of the fourth industrial revolution, has emerged as the main standard of service and resource delivery. As cloud computing has grown into a mature technology and is being rapidly adopted in many HEIs across the world, retaining customers of this innovative technology has become a challenge to the cloud service providers. Current research trends on cloud computing have sought to study the acceptance or adoption of technology; however, little research has been devoted to the continuance use in an organizational setting. To address this gap, this study aims to investigate the antecedents of cloud computing continuance use in HEIs. Hence, drawing on the prior literature in organizational-level continuance, this research established a conceptual model that extends and contextualizes the IS continuance model through the lens of the TOE framework (i.e., technological, organizational, and environmental influences). The results of a pilot study, conducted through a survey with information and communications technology (ICT) decision makers, and based on the proposed conceptual model, indicate that the instrument is both reliable and valid, and so point the way towards further research. The paper closes with a discussion of the research limitations, contribution, and future directions.

The tendency for internationalization of higher education in many Higher Education Institutions (HEIs) around the world, including those of Malaysia, is increasing with the current wave of globalization; however, the main challenge of international HEIs is how to manage intercultural diversity and overcome intercultural learning challenges that affect international students’ learning outcomes and learning sustainability. Hence, the aim of this study was to investigate intercultural learning challenges that affect international students’ learning sustainability through a proposed measurement model. The data were collected from 273 international students in Malaysian HEIs through a survey and were analyzed using variance-based structural equation modeling (i.e., PLS-SEM). The results showed that intercultural challenges did not have a significant effect on students’ learning sustainability. Nevertheless, language challenges, academic challenges, and research challenges were found to have a significant negative impact on the learning sustainability of international students. The study concluded that intercultural learning barriers are considered to be intercultural learning challenges, which have a negative effect on international students’ learning sustainability even though international students might overcome such challenges with the passage of time. In addition, the study identified different factors pertaining to international students’ learning sustainability, such as students’ language and learning skills, Higher Education Institutions’ educational systems, and lecturers. Based on the finding of the study, Higher Education Institutions need to create a clear framework that encompasses these factors to improve learning sustainability among international students.