Towards an Integrated Conceptual Model for Cloud Adoption in
Saudi Arabia
Nouf Alkhater
1
,
Victor Chang
2
, Gary Wills
1
and Robert Walters
1
1
Electronics and Computer Science, University of Southampton, Southampton, U.K.
2
Leeds Beckett University, Leeds, U.K.
Keywords: Cloud Computing, Adoption, Factors, TOE Framework.
Abstract: There are several advantages of utilising cloud computing in organisations such as cost saving and
flexibility in acquiring resources. The use of cloud computing in developing countries, such as Saudi
Arabia, is still in its early stages and has not been as widely adopted there as in developed countries. In fact,
moving a current system to the cloud depends on many factors that may affect a Saudi Arabian
organisation's decision to adopt the cloud. In order to encourage the adoption of cloud technology it is
essential to understand why some enterprises are more prepared than others to move to the cloud. Hence, the
aim of this research is to examine factors that might impact on a Saudi Arabian organisation's intention to
adopt cloud computing. In this paper, we propose a conceptual model which integrates aspects of the
Technology Organisation Environment (TOE) framework. The proposed model identifies the key factors
that might influence organisations to employ cloud services. Our findings show that all the proposed factors
in the cloud adoption model, except for competitive pressure and trading partner pressure, are statically
significant.
1 INTRODUCTION
Cloud computing is the emerging paradigm of
delivering IT services to end users as a utility service
over the Internet. A number of technologies are used
to make cloud computing happen, including
virtualisation and Web 2.0, and their presence makes
cloud computing more efficient and usable (Jeffery
and Neidecker-Lutz, 2010). The concept of cloud
computing started in the 1960s, but the expression
“cloud computing” became widely popular only in
2007 (Chen et al., 2010). A number of different
proposals, such as grid computing, have been
developed but none of them has achieved cloud
computing’s level of success in offering services to
the general public.
Cloud computing can bring several advantages to
organisations. The cloud can reduce capital
expenditure for both large and small organisations
and enable them to pay only for the services they
consume rather than setting up in-house IT
infrastructure (Buyya et al., 2009). Cloud computing
offers business opportunities and flexibility for
organisations to increase their revenues (Marston et
al., 2011). Despite all these benefits, some
organisations hesitate to migrate their work to the
cloud. To help organisations achieve their long-term
goals, a number of frameworks have been developed
to provide guidelines and recommendations for
cloud adoption, such as Chang et al., (2013) and
Chang (2015).
An interesting observation about the proposed
models and frameworks in previous studies is that
they focus on the costs and benefits of cloud
adoption. Furthermore, there is a lack of empirical
studies conducted to examine the influential factors
for adopting cloud technology at enterprise level
(Low et al., 2011; Borgman et al., 2013).
Additionally, all these adoption cases have focused
on deployment cases in the West; the adoption rate
in the Saudi Arabia is in the beginning phase. Hence,
the aim of this study is to carry out an in-depth
investigation of factors that influence an enterprise’s
decision to use cloud technology in Saudi Arabia.
An integrated conceptual model has been proposed
in order to identify what could drive an organisation
to use cloud services or prevent them from doing so.
The structure of the paper is as it follows.
Section 2 begins with the background of cloud
computing and then provides a critical review of the
80
Alkhater N., Chang V., Wills G. and Walters R..
Towards an Integrated Conceptual Model for Cloud Adoption in Saudi Arabia.
DOI: 10.5220/0005528400800085
In Proceedings of the 2nd International Workshop on Emerging Software as a Service and Analytics (ESaaSA-2015), pages 80-85
ISBN: 978-989-758-110-6
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
existing work and theories in order to identify
factors that affect an organisation’s decision to adopt
cloud computing. Section 3 presents the conceptual
model for cloud adoption in Saudi Arabia. The
research methodology is discussed in Section 4.
Section 5 provides the preliminary results. Finally,
the summary and future work are presented in
Section 6.
2 LITERATURE REVIEW
2.1 Benefits of Cloud Migration
This section presents the benefits for organisations
that adopt cloud computing. First, cloud computing
offers cost reductions and savings due to the
outsourcing of hardware and services. Organisations
can save on operational costs in that they no longer
have to buy machines, provide a bigger space for
storage, and pay upgrade costs and staffing costs
(Chang, 2015). The responsibilities and costs
involved in improving and upgrading systems are
managed by the cloud service providers (Armbrust
et al., 2010; Buyya et al., 2009; Jeffery and
Neidecker-Lutz, 2010). Secondly, cloud technology
provides an opportunity for organisations to scale
their services easily and tailor these to specific
needs. For example, customised functions can be
designed for the company staff so that they can
perform their tasks quickly and easily. Thirdly,
cloud computing supports green IT since the costs of
buying and maintaining servers are reduced with
fewer carbon emissions and less energy
consumption taking place (Buyya et al., 2012;
Marston et al., 2011). Additionally, enterprises can
design, build and run their applications more
smoothly, since they can be tested in virtual
machines as many times as they like. Finally, the
flexibility of delivering computing services can
drive organisations to migrate their services to the
cloud (Foster et al., 2008).
2.2 A Review of Proposed Approaches
to Cloud Migration
This section reviews existing work and models
related to the migration to cloud computing in order
to explore how far the security issues are considered
in them.
First, Khajeh-Hosseini et al., (2010) reported a
case study that refers to a legacy migration of system
in the gas and oil sector. This study examined the
migration of an IT system from an enterprise data
centre to Amazon’s EC2. The cost analysis of the
company is presented. In addition, the case study
presents the possible advantages and risks linked to
the migration of the system based on the point of
view of managers and other staff, except the security
manager and other security experts. In fact, the most
important views that need to be taken into account
for migration process are those of the security staff.
Their findings indicate that the use of cloud
infrastructure will decrease the enterprise’s costs.
Their results are also useful for decision-making
purposes as they will help analysts to find solutions
to upcoming issues associated with the adoption of a
cloud by enterprises. However, their work does not
take into account the security aspect. In fact, security
is a vital factor in cloud migration and it needs to be
considered as an essential element in the migration
process.
Khajeh-Hosseini et al., (2011a; 2011b) extended
their previous study to develop a toolkit that helps
decision-makers and organisations address their
concerns during the migration process; the toolkit
provides a framework that can be used to evaluate
the migration of businesses from a enterprise data
centre to a public cloud. The first tool consists of a
list of questions; this helps enterprises to determine
whether a public cloud is a suitable technology for
their IT system. The second tool is helpful for the
decision-makers in terms of estimating the costs of
employing a public cloud. Their third tool is a
spreadsheet that demonstrates the possible risks and
benefits associated with a public cloud from a
general organisational perspective. Their evaluation
of the tools based on different case studies focuses
only on the cost model. Indeed, the proposed
methods are a good starting point for risk assessment
and are useful for decision-makers as they cover
some issues regarding migration to a public cloud.
However, this work only considers the cost of the
infrastructure when using one type of cloud (the
public cloud).
Klems et al., (2009) proposed a framework to
measure the costs of using IT infrastructure in the
cloud. They compared it with conventional IT
approaches, such as the cost of setting up in-house
IT infrastructure or a grid computing service. They
dealt with costs in their framework under direct and
indirect costs. IT infrastructure resources are an
example of direct costs, whereas an indirect cost is
incurred by the failure to meet business goals and set
up training courses for the new technology. The
framework was evaluated based on two case studies.
However, their work was in the development phase
and therefore the results are not provided. Also, this
study did not consider the security aspect.
TowardsanIntegratedConceptualModelforCloudAdoptioninSaudiArabia
81
Hajjat et al., (2010) proposed a model for the
migration of an enterprise’s applications to a hybrid
cloud. The aim of this study was to identify the costs
and benefits of migrating part of the system to the
cloud. The effectiveness of this approach was briefly
evaluated based on a case study of the migration of
applications to the cloud. However, this work does
not mention how the cost can be computed and only
focuses on one type of cloud (the hybrid cloud).
They also did not consider the security aspect.
Hu and Klein (2009) have carried out a study to
investigate privacy issues during migrating e-
commerce applications to the cloud. Their study
suggests that the user’s data and critical business
information must be encrypted during the migration
process. The authors have also studied and
compared existing data encryption methods in
different layers (storage, database, middleware and
application). They argue that the middleware layer
encryption is the most effective approach for
migrating e-commerce applications to the cloud in
terms of performance. The evaluation of their work
was based on a case study for an e-marketplace
application. Indeed, this approach discussed data
encryption, particularly for the transmission of e-
commerce applications to the cloud. This method
helps to ensure privacy of data and provides
protection for applications during the migration
process. Nevertheless, the authors did not point out
how the data and applications would be migrated to
the cloud; they also ignored the other aspects of
security and privacy that need to be considered.
Hao et al., (2009) proposed a cost model that can
be used to determine the type of services included in
migration and their possible location. The model that
they developed used a genetic algorithm to provide
an effective decision for service migration, by
looking for the most optimal migration decisions. In
this study, besides considering the cost of service
migration, they evaluated the cost of consistency
maintenance and communication. It is important to
have strong decision support for the infrastructure
support, prior to migration. However, the authors
omit security in the migration process and they deal
only with the security aspect that involves accessing
the control process by proposed mutual
authentication using certificate authority.
Kaisler and Money (2011) have conducted a
study to investigate issues associated with service
migration to a cloud, as well as the security
problems involved with service implementation.
They considered several security challenges. It is
noticeable that this study simply lists the possible
challenges without any evaluation; it also ignores the
security aspects in the migration process.
2.3 A Review of Proposed Models for
the Adoption of New Technologies
This section describes relevant theories and
frameworks for the adoption of new technologies. It
includes the TOE framework, the Diffusion of
Innovations (DOI) theory and the institutional
theory, which have been widely adopted by
researchers.
Tornatzky and Fleischer (1990) proposed the
TOE framework to analyse the acceptance of new IT
technologies at an organisational level. The TOE
framework investigates the impact of three factors,
Technology, Organisation and Environment, on the
organisation’s decision to adopt a new technology.
According to Tornatzky and Fleischer (1990) and
Chau and Tam (1997), TOE can be summarised as
follows:
The technology aspect describes the internal and
external characteristics of the new technology
and how adopting a new technology can
influence the organisation.
The organisational context is focused on
different measures that can influence the
direction of the organisation, for example, firm
size and scope of interests.
The environmental context refers to the
characteristics of the environment where an
organisation operates its business and might have
a significant impact on their decision.
Government regulation and competitors are an
example of the environmental context.
The DOI was proposed by Rogers (1995). DOI is a
widely used theory in information system research to
examine user acceptance of new ideas and
technologies. The DOI theory presents five attributes
that have a direct influence on adoption rate: relative
advantage, complexity, compatibility, trialability and
observability.
The institutional theory is one of the common
theories usually used for explaining the adoption of
IT technologies (Scott and Christensen, 1995; Scott,
2001). The different between the TOE framework
and institutional theory is that institutional theory
contains two important elements (trading partner
pressure and competitors) in the environmental
context of the TOE framework which might play an
important role in an organisation’s decision to adopt
new technologies.
The other models which have been built based on
previous theories in order to identify the factors that
affect on a firm's decision to implement cloud
computing are presented in a previous work
ESaaSA2015-WorkshoponEmergingSoftwareasaServiceandAnalytics
82
(Alkhater et al., 2014).
3 CONCEPTUAL MODEL
As discussed in Section 1, some of the proposed
frameworks and models do not fully address the in-
depth investigations on what factors influence cloud
adoption for organisations. The TOE framework has
been widely adopted and is a suitable model for
improvement since it has a proven track record of
successful integration (Tornatzky and Fleischer,
1990; Chau and Tam, 1997). Additionally, another
benefit of using the TOE framework is that this
framework predicts and examines the adoption of
technology based on three aspects: technology
context, organisation context and environment
context.
In this paper, an integrated model has been
proposed to identify factors that impact on an
enterprise’s intent to adopt the cloud services in
Saudi Arabia. The initial model has been constructed
by integrating aspects of the TOE framework and
combining the most important factors from the DOI
theory and institutional theory along with other
factors (trust, privacy and physical location) that
have not yet been investigated in any previous
studies as main factors that may have an impact on
the organisation’s decision to adopt cloud services.
The conceptual model for cloud computing adoption
in Saudi Arabia is presented in Figure 1. Moreover,
Table 1 identifies factors involved in the cloud
adoption model; the details of these proposed factors
were discussed in a previous work (Alkhater et al.,
2014).
Table 1: The factors identified for cloud adoption.
Factors Sub-dimensions
Technological Factors
Availability
Reliability
Security
Privacy
Trust
Relative advantage
Compatibility
Complexity
Organisational Factors
Top management support
Organisation size
Technology readiness
Environmental Factors
Compliance with regulations
Competitive pressure
Trading partner pressure
Physical location
Figure 1: A conceptual model for cloud computing
adoption.
4 METHODOLOGY
An expert review is a simple method that enables
researchers to collect data from experts who have
knowledge of the topic under study. This technique
can be used in quantitative, qualitative or mixed
methods at different stages of the study (Tessmer,
1993). In this initial study, semi-structured
interviews were used for collecting data from twenty
IT experts working in IT departments in different
Saudi organisations. The study population includes
IT staff or managers. The aim of the interviewing IT
experts was to review factors that were previously
identified in Section 3. A second objective was to
discover other factors left unstated in former studies.
The interviewees in this study were working in
various sectors, such as petrochemicals, oil and gas
and engineering, in large organisations and small
and medium-sized enterprises with at least five
years’ working experience in IT. Seven of the
participants in this study were working in companies
that had already adopted cloud computing, while
thirteen (65%) of them were not.
5 RESULTS
This section shows the results of this preliminary
study. In this study the participants were asked
closed-ended questions about all the factors which
were stated previously in Section 3. The purpose of
the questions was to measure the importance of the
identified factors in the proposed model for cloud
adoption from an expert perspective. The closed-
ended questions were designed using a five-point
TowardsanIntegratedConceptualModelforCloudAdoptioninSaudiArabia
83
Likert scale, which ranged from 5 (very important)
to 1 (not relevant). SPSS software was used to
analyse the collected data from IT experts; the test
value was identified as 3. Table 2 presents the
results of using the one-sample t-test.
In this study Bonferroni correction was used for
controlling for false positive results by dividing
alpha (α) by the number of factors included in the
questionnaire.
(α/n) = 0.05/15 = 0.0033 (1)
Table 2: One-sample t-test.
Factors p-value Result
Availability <0.001
Statistically
significant
Reliability <0.001
Statistically
significant
Security <0.001
Statistically
significant
Privacy <0.001
Statistically
significant
Trust <0.001
Statistically
significant
Relative advantage <0.001
Statistically
significant
Compatibility <0.001
Statistically
significant
Complexity <0.001
Statistically
significant
Top management support <0.001
Statistically
significant
Organisation size .003
Statistically
significant
Technology readiness <0.001
Statistically
significant
Compliance with regulations <0.001
Statistically
significant
Competitive pressure .008
Not statistically
significant
Trading partner pressure .148
Not statistically
significant
Physical location <0.001
Statistically
significant
It is interesting to note that most of organisations
taking part in this preliminary study were concerned
about privacy, security and trust issues and this was
one of the major reasons behind their decisions not
to use cloud services. Furthermore, there were other
factors that were suggested by experts, such as
compatibility, compliance with regulations and cost
savings, and organisations need to take these into
account before employing the cloud services. Most
of these factors already exist in the proposed model
for cloud adoption.
In order to measure the reliability of the results,
Cronbach's alpha was used in this initial study.
According to Hinton (2004) and Field (2009), a
value from 0.9 and above is considered highly
reliable and from 0.7 to 0.8 is acceptable. The
Cronbach’s alpha coefficient of this study was
0.719, which is considered to be an acceptable value.
6 CONCLUSIONS
The great benefit of cloud technology is that the
cloud offers resources to multiple users at any time
in a dynamic way and according to user needs. In
addition, users only pay for the services that they
consume. However, despite the fact that the cloud
offers various benefits for enterprises, from
flexibility to cost reduction, moving data from an in-
house data centre to the cloud is not a simple task.
Therefore, this study seeks ways to encourage
organisations to adopt cloud services in Saudi
Arabia as well as to investigate the factors that affect
the implementation of this technology. This paper
presents the initial model for cloud adoption in
Saudi Arabia and in future a survey will be
conducted to validate the developed model. Further
outcomes will be published shortly.
REFERENCES
Alkhater, N., Wills, G. & Walters, R. 2014. Factors
influencing an organisation's intention to adopt cloud
computing in Saudi Arabia. IEEE 6
th
International
Conference on Cloud Computing Technology and
Science, pp. 1040–1044.
Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz,
R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A.,
Stoica, I., et al. 2010. A view of cloud computing.
Communications of the ACM, 53, pp. 50–58.
Borgman, H. P., Bahli, B., Heier, H., & Schewski, F.
2013. Cloudrise: exploring cloud computing adoption
and governance with the TOE Framework. 46
th
Hawaii
International Conference on System Sciences, pp.
4425–4435. IEEE doi:10.1109/HICSS.2013.132.
Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J.
&Brandic, I.2009. Cloud computing and emerging IT
platforms: Vision, hype and reality for delivering
computing as the 5th utility. Future Generation
Computer Systems, 25(6), pp. 599–616.
Buyya, R., Calheiros, R. N. & Li, X. 2012. Autonomic
cloud computing: Open challenges and architectural
elements. 2012 Third International Conference on
Emerging Applications of Information Technology, pp.
3–10. doi:10.1109/EAIT.2012.6407847.
Chang, V., Walters, R. J., & Wills, G. (2013). The
development that leads to the Cloud Computing
Business Framework. International Journal of
Information Management, 33(3),pp. 524-538.
Chang, V. (2015). A proposed Cloud Computing Business
ESaaSA2015-WorkshoponEmergingSoftwareasaServiceandAnalytics
84
Framework. ISBN: 9781634820172 (print), Nova
publisher.
Chau, P.Y.K. and Tam, K.T. 1997. Factors affecting the
adoption of open systems: An exploratory study.MIS
Quarterly, 21(1), pp. 1–24.
Chen, X., Wills, G., Gilbert, L. and Bacigalupo, D. 2010.
Using cloud for research: A technical review. JISC
Final Report.
Field, A. 2009. Discovering statistics using spss. 3
rd
ed.
Thousand Oaks, CA: Sage Publication.
Foster,I., Zhao, Y., Raicu, I.& Lu, S. 2008. Cloud
computing and grid computing 360- degree compared.
In: Grid Computing Environments Workshop
(GCE’08), IEEE Press, pp. 1–10.
Hajjat, M., Sun, X., Sung, Y.W.E., Maltz, D., Rao, S.,
Sripanidkulchai, K. & Tawarmalani, M. 2010.
Cloudward bound: Planning for benecial migration
of enterprise applications to the cloud. ACM
SIGCOMM Computer Communication Review, 40(4),
pp. 243–254.
Hao, W., Yen, I.-L. & Thuraisingham, B. 2009. Dynamic
service and data migration in the cloud. 33
rd
Annual
IEEE International Computer Software and
Applications Conference, pp. 134–139.
doi:10.1109/COMPSAC.2009.127.
Hinton, P. 2004. Statistics Explained: A Guide for Social
Science Students. 2
nd
ed. Taylor & Francis.
Hu, J. & Klein, A. 2009. A benchmark of transparent data
encryption for migration of web applications in the
cloud. 2009. Eighth IEEE International Conference on
Dependable, Autonomic and Secure Computing, pp.
735–740. doi:10.1109/DASC.2009.85.
Jeffery, K. and Neidecker-Lutz, B. 2010. The future of
cloud computing opportunities for European cloud
computing beyond. Expert Group Report, Public
Version 1.0.
Kaisler, S. and Money, W. H. 2011. Service migration in a
cloud architecture. 44
th
Hawaii International
Conference on System Sciences, pp. 1–10.
doi:10.1109/HICSS.2011.371.
Khajeh-Hosseini, A., Greenwood, D. &Sommerville, I.
2010. Cloud migration: A case study of migrating an
enterprise IT system to IaaS. IEEE 3
rd
International
Conference on Cloud Computing, Cloud 2010, pp. 5–
10, July 2010: Miami, FL, USA.
Khajeh-Hosseini, A., Sommerville, I., Bogaerts, J. &
Teregowda, P. 2011. Decision support tools for cloud
migration in the enterprise. IEEE 4
th
International
Conference on Cloud Computing, pp. 541–548,
(Khajeh-Hosseini et al. 2011a).
Khajeh-Hosseini, A., Greenwood, D., Smith, J. W.
&Sommerville, I. 2011. The cloud adoption toolkit:
Supporting cloud adoption decisions in the enterprise.
Software: Practice and Experience, 42(4), (Khajeh-
Hosseini et al. 2011b).
Klems, M., Nimis, J. & Tai, S. 2009. Do clouds compute?
A framework for estimating the value of cloud
computing. Designing E-Business Systems. Markets,
Services and Networks, pp. 110–123. Springer Berlin
Heidelberg.
Low, C., Chen, Y. & Wu, M. 2011. Understanding the
determinants of cloud computing adoption. Industrial
Management & Data Systems, (111)7, pp. 1006–1023.
doi:10.1108/02635571111161262.
Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J. &
Ghalsasi, A. 2011. Cloud computing—The business
perspective. Decision Support Systems, (51)1, pp.
176–189. doi:10.1016/j.dss.2010.12.006.
Rogers, E. M. 1995. Diffusion of innovation. 4
th
ed. New
York, NY: The Free Press.
Scott, W.R. and Christensen, S. 1995. The institutional
construction of organizations: International and
longitudinal studies. Thousand Oaks, CA: Sage.
Scott, W.R. 2001. Institutions and organizations. 2
nd
ed.
Thousand Oaks, CA:Sage.
Tessmer, M. 1993. Planning and conducting formative
evaluations. London: Kogan Page.
Tornatzky, L.G. and Fleischer, M. 1990. The process of
technological innovation. Lexington, MA: Lexington
Books.
TowardsanIntegratedConceptualModelforCloudAdoptioninSaudiArabia
85