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An Analysis of the Factors Affecting the Adoption of Cloud Computing in Higher Educational Institutions: A Developing Country Perspective

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Abstract

This article aims to examine the main factors that may hinder or facilitate the adoption of cloud computing (CC) services by higher educational institutions in developing countries, exemplified here by Oman. A conceptual model was developed through extending the technology-organization-environment (TOE) framework. Data was collected from 387 IT decision makers working in four higher educational institutions in Oman using a cross-sectional survey. Data was analysed using structural equation modelling based on AMOS 22.0. The results show that behavioural intention (BI) towards adopting CC services in higher educational institutions was influenced by top management support, relative advantage, attitudes towards change, technology readiness, complexity, government regulation, peer pressure, and data concerns in their order of influencing power. These all together accounted for 58.3% of the variance in BI. However, compatibility, vendor lock-in and external expertise did not have an influence on BI. This research provides original insight for cloud computing adoption within Oman from a managerial and IT professional perspectives. Specifically, this research would be helpful for government agencies, cloud computing providers and policy makers at higher educational institutions. It will also explain the relatively low penetration rate of cloud computing services at present, which will help in formulating strategies to encourage the adoption and acceptance of CC services by Omani higher educational institutions, where CC is still considered an innovation.
DOI: 10.4018/IJCAC.2018100104
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Volume 8 • Issue 4 • October-December 2018
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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
Ali Tarhini, Department of Information Systems, College of Economics and Political Science, Sultan Qaboos University,
Muscat, Oman
Khamis Al-Gharbi, Department of Information Systems, College of Economics and Political Science, Sultan Qaboos
University, Muscat, Oman
Ali Al-Badi, Department of Information Systems, College of Economics and Political Science, Sultan Qaboos University,
Muscat, Oman
Yousuf Salim AlHinai, Department of Information Systems, College of Economics and Political Science, Sultan Qaboos
University, Muscat, Oman

This article aims to examine the main factors that may hinder or facilitate the adoption of cloud
computing (CC) services by higher educational institutions in developing countries, exemplified
here by Oman. A conceptual model was developed through extending the technology-organization-
environment (TOE) framework. Data was collected from 387 IT decision makers working in four
higher educational institutions in Oman using a cross-sectional survey. Data was analysed using
structural equation modelling based on AMOS 22.0. The results show that behavioural intention (BI)
towards adopting CC services in higher educational institutions was influenced by top management
support, relative advantage, attitudes towards change, technology readiness, complexity, government
regulation, peer pressure, and data concerns in their order of influencing power. These all together
accounted for 58.3% of the variance in BI. However, compatibility, vendor lock-in and external
expertise did not have an influence on BI. This research provides original insight for cloud computing
adoption within Oman from a managerial and IT professional perspectives. Specifically, this research
would be helpful for government agencies, cloud computing providers and policy makers at higher
educational institutions. It will also explain the relatively low penetration rate of cloud computing
services at present, which will help in formulating strategies to encourage the adoption and acceptance
of CC services by Omani higher educational institutions, where CC is still considered an innovation.

Cloud Computing, Developing Countries, Education, Environmental Context, Higher Educational Institutions,
Organizational Context, Technology Adoption, Technology Context, TOE Framework, Universities

Volume 8 • Issue 4 • October-December 2018
50
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Technology today is one of the most important elements of development in various sectors (Gangwar,
Date & Ramaswamy, 2015). As a result of the interest in technology around the world, all organization
and information technology managers try to implement new technologies that help them to improve
the quality of their work, increase the productivity, reduce the cost and increase the benefits (Arvanitis
et al., 2017). A new technology concept has emerged which is termed CC. Cloud Computing refers to
both the applications delivered as services over the Internet and the hardware and systems software
in the data centres that provide these services. Some researchers define CC as an updated version of
utility computing. For example, Arpaci (2016) describes CC as a distributed computing technology
that provides dynamically scalable computing resources including storage, computation power, and
applications delivered as a service over the Internet.
The cloud-based services free organizations in setting up IT infrastructure by allowing them to
use services and pay the charges only for the extent of the usage (Lal, 2015; Ratten, 2015). CC has
advantages of location independence, cost effectiveness, maintenance, and scalability which support
the organization’s approach in sustaining competitive advantages (Tariq et al., 2017; Priyadarshinee,
2018). However, there are some barriers that may hinder the adoption of CC services (e.g. security,
privacy, trust, compatibility, and data concerns) (Priyadarshinee et al., 2017; Gupta et al., 2017; Palos-
Sanchez & Correia, 2018). Other factors slowing the adoption of CC services include lack of top
management support, vender lock-in and external expertise (Alharthi et al., 2017; Loukis et al., 2017).
In recent years the Internet has accelerated the use of cloud services to support the educational
online system. CC is known as a recent model that enables users to have computing resources on
demand and pay by use (Sultan, 2010). It has been used widely in education; educators and students
store and share their data widely in the cloud (Sultan, 2010). Nowadays data can be stored in the
cloud enabling its access to be more flexible. CC has changed the structure and elements of high
education in a positive way. Furthermore, the CC is beneficial to students in terms of flexibility,
scalability, and supporting online learning (Sabi, 2016). Once CC services such as Google Drive,
Dropbox, SkyDrive, and iCloud are integrated into educational settings the learner can have a
learning advantage in terms of performance, effectiveness, and efficiency (Oliveira et al., 2014).
The availability, flexibility, and ease of use are other benefits of CC in higher education (Lee, 201;
Haffar et al., 2017). In addition, CC adoption in educational institutions has reduced the research and
learning cost through IT infrastructure, data centres and applications (Sultan, 2010). For instance,
various IT services can be rented at The Washington State University in USA (Sultan, 2010). CC in
the US educational sector has improved efficiency, reduced costs and provided convenience (Yatim,
2016). For example, Microsoft live @edu provides student access to email, Office package, as well
as SkyDrive (Yatim, 2016). The University of California (UC), Berkeley used CC on developing and
deploying SaaS Applications for different courses (Alshuwaier et al., 2012).
CC services has been employed in different sectors such as e-government (Mohammed et al., 2016;
Priyadarshinee et al., 2017), SMEs (Ross & Blumenstein, 2015; Loukis et al., 2017), banking (Asadi
et al., 2017), manufacturing (Oliveira et al., 2014; Gupta et al., 2017), and tourism (Palos-Sanchez &
Correia, 2018). However, the CC services in higher educational institutions are still limited and more
specifically in the context of developing countries (Shin, 2013, Tashkandi & Al-Jabri, 2015; Yuvaraj,
2016). Ibrahim et al. (2015) conducted a systematic literature review about CC in higher educational
institutions, and found that the universities were interested in adopting them in their education
systems; however, there is a dearth of empirical studies that focus on the adoption and acceptance of
CC services by universities. Universities in developing countries have started implementing CC in
higher education but the progress in the Middle East countries is still in its infancy when compared
to western universities (Odeh, Warwick, & Cadenas, 2014; Tashkandi & Al-Jabri, 2015).
Oman, as a prominent country in the GCC in Middle East, was selected for this study as Omani
universities are investing heavily in modern technologies to improve their educational systems (Al-
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In many developing countries such as Saudi Arabia the adoption of cloud computing is still at an early stage. This research aims to investigate the influencing factors in the decision to adopt cloud computing in the private sector. An integrated model is proposed incorporating critical factors derived from a literature review, along with other factors (such as physical location) that have not been examined in previous studies as main factors in the organisation's decision to adopt cloud services. Data were collected from 300 IT staff in different organisations in the private sector in Saudi Arabia, in order to test the cloud adoption model and explore factors that were positively or negatively associated with cloud adoption. The most influential determinants of cloud adoption were found to be quality of service and trust. However, security and privacy concerns still prevent cloud adoption in this country. This study also showed that the effect of these variables differed according to organisation size and in adopter and non-adopter companies. Overall, these research findings provide valuable guidelines to cloud providers, managers, and government policy makers on ways of encouraging the spread of cloud computing in Middle Eastern countries and increasing its implementation, particularly in Saudi Arabia.
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Along with water, gas, electricity, and telephone, cloud computing has been considered as the fifth utility. Like other utility services available in today's social computing services are readily available on demand (Buyya, Yeo, Venugopal, Broberg, & Brandic, 2009). The purpose of the study is to develop a hybrid two-stage, structural equation modeling (SEM) – artificial neural network (ANN) model to predict motivators affecting cloud computing adoption services in the Indian private organizations. This research article proposes a new paradigm by extending the Technology Organization Environment Model (TOE) with external factors, namely, perceived IT security risk and risk analysis for the first time in a technology adoption study. One of the core contributions of the study is the introduction of new factors, perceived IT security risk and risk analysis. Data were collected from 660 professional experts and analyzed using structural equation modeling (SEM) and artificial neural network (ANN) modeling. The SEM results showed that perceived IT security risk (PITR), risk analysis (RA), technology innovation (TI), management style (MS) and trust (T) have a significant influence on cloud computing adoption. The only exceptions were the usage of technology (UT) and industry usage (IU) which witnessed statistically insignificant influence on cloud computing adoption. Furthermore, the results obtained from SEM were employed as input to the artificial neural network (ANN) model and results showed that ‘trust’, ‘perceived IT security risk’, and ‘management style’ as most important predictors in cloud computing adoption.