Cloud Computing Financial and Cost Analysis: A Case Study of
Saudi Government Agencies
Mohammed Mreea, Kumudu Munasinghe and Dharmendra Sharma
Faculty of Education,Science,Technology and Mathematics, University of Canberra, ACT, Australia
Keywords: Cloud Computing, Return on Investment (ROI), Total Cost Ownership (TCO), Data Centre Variable Cost
(DCVC), Data Centre Fixed Cost (DCFC).
Abstract: Cloud computing is an innovation in world technology. It is used to provide organization services as a
utility service through internet and the innovative uptake of cloud for improved effectiveness and efficiency.
There is an absence of academic studies about the financial feasibility and implementation cost government
agencies to take up the cloud by government agencies. This paper seeks to identify the cloud computing
financial indicators and implementation cost variables which are relevant to public organizations. The
proposed model consists of Saudi case study findings based on analysis of evidence from Saudi government
organizations. Random samples from different categories of professionals in Saudi Arabia participated in
the questionnaire to extract and confirm the financial indicators and implementation cost variables. The
results indicate a return on investment (ROI) and total cost ownership (TCO) are the main financial
indicators to study cloud adoption. Also, data centre variables and fixed cost parameters play a main role in
calculating the cloud implementation cost.
1 INTRODUCTION
Improving the public sector’s services is one of the
top priorities for many governments and
organizations. Most of the transactional systems in
government agencies in the Kingdom of Saudi
Arabia are not fully operable because the idea of
applying and implementing government services is
not practical and a large budget is needed to
implement agency services such as email. Thus,
cloud computing and its elastic commercial model of
information technology possession, such as data
storage or providing computing power on the
mandate, promises to provide assistance and many
rewards for governments and organizations.
There are financial benefits for Saudi public
organizations if they decide to adopt cloud
computing. First, reducing capital investment is the
transformation which spent on IT infrastructure
“capital expenditure to operational expenditure
(Herbert and Erickson 2009). Second, costs are
reduced costs as infrastructure maintenance costs are
Lower and more efficient than traditional computing
(McDonald, MacDonald et al. 2010). Third,
decreased energy consumption due to moving IT
infrastructure to cloud providers, can leading to
greener organizations. Fourth, decrease in physical
space requirements leading to reduced real estate
expenses. Finally, it enables organizations to create
on-demand pricing models for their products.
However, there are no studies until now about
the feasibility of adopting cloud computing in Saudi
Arabia. Thus, it is necessary to study the feasibility
of adopting cloud computing and the cost of
implementing in Saudi Arabia public sector. This
paper will focus to identify financial indicators
attributes and variables cost of implementation.
2 ADVANCES IN CLOUD
COMPUTING
2.1 Cloud Computing
Cloud computing (CC) has been defined in a variety
of ways. It can be explained as a system that enables
resource sharing management by using fewer
resources and efforts (Wen and Chen 2010). Alharbi
asserts that CC facilitates changing software,
Mreea M., Munasinghe K. and Sharma D.
Cloud Computing Financial and Cost Analysis: A Case Study of Saudi Government Agencies.
DOI: 10.5220/0006300804590466
In Proceedings of the 7th International Conference on Cloud Computing and Services Science (CLOSER 2017), pages 459-466
ISBN: 978-989-758-243-1
Copyright
c
2017 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
459
infrastructure, and platforms and allows them to be
offered as services to users (Ahuja, Yang et al.
2009). The US National Institute of Standards and
Technology (NIST) defined CC as “a model for
enabling convenient, on-demand network access to a
share pool of configurable computing resources
(e.g., networks, servers, storage, applications, and
services) that can be rapidly provisioned and
released with minimal management afford or service
provider interaction”(Mell and Grance 2010). Figure
1 represents the NIST cloud computing concept
schema. Industries such as banking and health care
are moving towards cloud technology because it
increases efficiency and provides accessibility
through any portable device(Morgan and Conboy
2013). The lack of resources in some countries can
be handled using cloud technology (Misra and
Mondal 2011) since because it costs less than
traditional infrastructure installations, CC allows
higher user accessibility. Cloud computing delivers
many benefits to organizations. The biggest of these
are high elasticity and huge cost reserves due to the
on-demand provision of services and its charging
model (Bhisikar 2011). Cloud computing also
provides an extensive range of advantages such as
increased flexibility, access anywhere, elastic
scalability, pay-as-you-go charging, simplicity and
distributed data centers.
Figure 1: NIST cloud computing concept schema (Alharbi
et al. 2015).
2.2 Cloud Computing Platforms
Industry investigators have made strong forecasts on
how Cloud technology will change the industry.
Buyya et al. (2009) recognized Cloud technology as
one of the noticeable innovation patterns (Buyya,
Yeo et al. 2009). As the assuming business shifts to
giving Platform as a Service (PaaS) and Software as
a Service (SaaS) for ventures and buyers to access
on interest paying little attention to area and time,
there will be a growth in the quantity of Cloud
stages accessible. As of late, a few modern
associations have started creating and exploring
innovations and bases for Cloud Computing. There
are many of providers for cloud platforms. For
example Amazon, Microsoft, Sun network, Aneka,
HP, Oracle, Citrix, and Scaleway. In this area, we
explore famous and oldest Cloud platforms.
Amazon Elastic Compute Cloud (EC2)
(Amazon, 2016) offers Machine Image (AMI)
having the libraries, applications, information and
related design settings or select from a library of all
around accessible AMIs. It has a virtual environment
that allows a user to run Linux-based applications.
The user can consider his needs to transfer to this
platform by choosing AMIs.
Google App Engine (Google, 2016) allows a user
to run web applications by utilizing the Python
programming language. Google App Engine also
supports Application Programming Interfaces (APIs)
for the Google Accounts, data store, and picture
control and email administrations. Additionally,
Google App Engine gives an online Administration
Console for the user to deal with the user running
web applications dynamically.
Microsoft Azure (azure, 2016) intends to
provide a coordinated improvement, facilitating, and
control Cloud figuring environment so that product
designers can without much of a stretch, make, have
overseen and scale both The Web and non-web
applications through Microsoft server farms. To
accomplish this point, Microsoft Azure backings a
far-reaching accumulation of restrictive
improvement apparatuses and conventions which
comprise Live Services, Microsoft.NET Services,
Microsoft SharePoint Services, Microsoft SQL
Services, and Microsoft client relationship
management CRM Services. Microsoft Azure
additionally bolsters Web APIs, for example, SOAP
and REST to permit programming engineers to
interface between Microsoft or non-Microsoft
instruments and advances.
Aneka is being supported through Manjra soft, is
a.NET-based administration (Chu, Nadiminti et al.
2007). It is planned to bolster different application
models and security arrangements. To create an
Aneka Cloud, the administration provider just needs
to configure Aneka platform, facilitating necessary
administrations on each selected desktop PC. The
motivation behind the Aneka platform is to in state
administrations and operates as a private point for
communication with whatever remains of the Aneka
Cloud. Aneka gives service level agreement SLA
with full support to help the client to indicate quietly
CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science
460
of services QoS prerequisites. Finally, the client can
to arrange and correspond on the QoS necessities to
be given by the administration provider (Venugopal,
Buyya et al. 2006).access the Aneka Cloud remotely
through the Gridbus website. The Gridbus is an
intermediary to allow the client to arrange and
correspond on the QoS necessities to be given by the
administration provider (Venugopal, Buyya et al.
2006).
2.3 Cloud Computing Adoption in
Saudi Government
According to International Data Corporation (2016),
Saudi Arabia individuals, private and small
organizations invested on cloud services about $50.4
million in 2014. And they expect to reach $77.4
million in 2016. Most of their requirements were
email, communication and collaboration, and
content management. However, government entities
are the biggest resistors to adopt cloud (IDC 2016).
Because there is no visible plan to implement any
cloud computing solutions in the government sector
due to the overly bureaucratic structure of the
multiple sectors and layers of the existing
government machinery. The major push and
initiative from someone in a position of authority or
a member of the royal family is a prerequisite before
the Saudi government would take a strategy to
discover the essential benefits offered by cloud
computing solutions to stakeholders. Also, the lake
of awareness and security issues other reasons for
this resistance.
Cloud computing is still in its beginning stages,
There is a few studies conduct in the Saudi context.
Chanchary and Islam (2011) observed a
phenomenon of striking inefficiency in Saudi Arabia
during their research on existing e-government
systems. They recommended that incorporating a
software-as-a-service (SaaS) layer would greatly
improve e-governance efficiency and help users in
their decision-making processes. They suggested
that this additional layer would facilitate better
access to information. The study concluded with the
assertion that this integration would help improve
any e-government services provided. Moreover, the
technology acceptance model (TAM) proposed by
Alharbi (2012) can be used to assess acceptance
levels in an organization. A study found that the
acceptance rates for cloud computing were highly
dependent on users’ ages, attitudes, jobs and
educational backgrounds (Alharbi 2012). Yamin
(2013) completed a survey of cloud computing
awareness in Saudi Arabia from an organization
level view. The study showed that cloud
technologies will be a new trend for Saudi’s
organizations. Alkahter (2014) was identifying the
factors with the most influence on the intention of
private organizations in Saudi Arabia to adopt cloud
services. This study found that the factors of
reliability, complexity, availability, privacy and
others had a significant impact on the decision to
adopt cloud computing.
By critiquing the previous studies, there was the
absence of theoretical and empirical studies
concerning the adoption in government sector in the
developing countries specify in Saudi Arabia. Public
organizations’ business initiatives are different and
more complex than a private organization.
Researchers have emphasized the need for an
increased focus on how organizations adopt
innovations (Mohammed and Ibrahim 2014). Some
researchers recommended applying theoretical
models and empirical studies for cloud adoption
decisions because there is a shortage of research in
this area (Mohammed and Ibrahim 2014).
Furthermore, no study to date has investigated and
analysed the financial data to invest in cloud
computing implementation. Thus, more financial
data analytics is important to contribute to the
research.
2.4 Proposed Financial Cloud
Computing Model for Saudi
Government
The author addresses the need to find the main
financial indicators and implementation cost
variables which impact on the organization to adopt
the cloudbased on survey analyses. The author
conducted one case of participants’ who responded
to the survey to clarify their responses.
2.4.1 Case Study
I analyzed one of the Saudi government
organization’s stories regarding the adoption of
cloud services. This organization is a part of the
education and training sector in Saudi Arabia. They
have recently implemented the cloud email service
package of Google “Google Apps Suite.” This
organization manages about 32 faculties over the
Kingdom of Saudi Arabia. They have more than
1000 staff. I interviewed an IT lecture’s who was
working as an IT senior in this organization’s data
center to clarify his survey responses. He told me
Cloud Computing Financial and Cost Analysis: A Case Study of Saudi Government Agencies
461
about their obstacles in providing email services to
all the staff in this organization. The main obstacles
were: availability, they could not guarantee the
availability of email service. Also, this service
remained offline for a long time until they fixed it.
The reasons behind that were that had no qualified
people to manage it, shortages in support contracts
and lack of financial resources. Sometimes, they had
asked IT academic staff to work with them as IT
supports staff to help them.
Also, they faced many issues with security
patches and limitations in storage. Finally, they
faced an issue with data centre space and the growth
in a number of servers. This negatively impacted on
the environment and space. Moreover, the increasing
maintenance and upgrade costs were too high for the
organization.
Based on these issues and the increasing demand
for email services of organizational staff, the
organization thought seriously about adopting a
cloud to provide this service to its employees. This
decision required costs to implement such as
hardware and software platforms, licenses, and
storage and network devices. Also, they paid for
additional services such as consultation and
migration services and maintenance contracts. But
the return on the investment in the long term was
better than the current situation.
After adopting the email service via the cloud,
they noted the difference between in-house email
and cloud email. They achieved many benefits:
efficiency in their services; availability 24/7, greater
mailbox size, and good security management with
advanced hardware. Also, they gained many of the
financial benefits. For example, decrees in TCO and
ongoing support cost compared with in-house
solution. Maintenance and development costs
decreased.Also, increase on ROI percentage. They
also gained competitive support via qualified people
from the provider and saved the organization space
to use as its training centers for students. Also, by
transferring this headache to qualified providers
simplified their business model and saved the
organization budget. Finally, by decreasing the
number of servers, the organization contributed to a
cleaner environment.
2.4.2 Analysis of Case Studies
A closer look at the case study from a financial
angle, the decision to adopt Googles cloud
computing services through a cloud provider was a
result of major organizational changes to help them
face financial and growth challenges. Thus, the
organization fixed the challenges by migrating their
services to the cloud. This impacted financially on
the organization budget.
The key points that can be understood from this
case study are the following:
- Cloud computing is an optimal option when
the budget is not going well in the organization
- The organization achieved some of the
financial indicators such as ROI, TCO.
- There was a positive ROI of adopting
Googles cloud computing services.
- The TCO for organization data center
decreased. This impacted on ongoing support
cost for the data center.
- The hardware requirements such as servers
can be simply configured and adjusted to meet
the organization's growth and demand under
the cloud computing model. And cloud
providers can provide hardware platform
services with least amount of management
overhead.
- The cloud computing facilitates "pay per use"
capability to organizations. This lead to the
organization having the flexibility to use
appropriate bandwidth based on their
objectives.
- The Software requirements such as email can
be scale up or down in relation to the current
demand by applications hosted on the cloud
platforms.
- Cloud computing can support decreasing
variable and fixed infrastructure costs
significantly. Thus, the saving cost is one of
key tipping point parameters to adopt cloud.
- The organization decision to adopt cloud
Leeds to reducing the creating a new data
centers. This impacted positively on saving
fixed costs.
- The organization decision to implement cloud
needs a specific budget. But the return on the
investment in the long term was better than
their previous situation.
- It can conclude some of their data center
implementation costs such as hardware and
software platforms, licenses, storage, network
devices, consultation and migration services
and maintenance contracts (SLA).
Finally, it can conclude the following
equations to calculate data center fixed and
variable implementation costs.


DCVCost= DCVCost1+ ……..+DCVCost n
CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science
462


DCFCost= DCFCost1+…...+ DCFCost n
The previous equations can help the organization
to calculate any cloud services cost in both
approaches private and public cloud. If the
organization decide to implement private cloud to
provide any service, then it should be responsible for
the whole cost for different delivery models such as
infrastructure, platform, and software to make this
service workable. Thus, in this case, the cost will be
expensive.
However, the public cloud will be cheap, and the
organization can only pay based on its usability.
Also, the previous equation can help to calculate this
cost.
Based on above case study analysis, figure 2
clears proposed a model for financial indicators and
data centre implementation cost.
Figure 2: Proposed model.
3 VALIDATING THE CASE
STUDIES FINDINGS
The authors continued to validate the proposed
models. They have investigated several research
methods to complete this. They have decided the
survey method is the good instrument to achieve it.
They have produced a comprehensive survey. The
questions are formatted to use a five-point Likert
scale to gather participants inputs, which ranged
from 1 (strongly disagree) to 1 (strongly agree). The
survey consists of 46 questions. The collected data
was analyzed by SPSS via regression model.
This study was conducted decision makers,
information technology (IT) managers and experts at
government organizations in Saudi Arabia. The
objective of this survey was to validate and improve
the proposed financial model. Most of the
participants in this survey were heads of IT
department and IT managers. Therefore, they had
the capability to recognize the future trends and
current situation of their organizations.
4 DATA RESULTS AND
ANALYSIS
4.1 Data Reliability
The test of measurement model will include the
estimation of internal consistency and the
convergent and discriminant validity of the
instrument items. Cronbach's alpha coefficient,
whose value ranges from zero (unreliable) to one
(perfectly reliable), is used to examine the reliability
of the survey instrument (Hair et al. 2006). The
Cronbach's alpha value in this survey is 0.738. Thus,
the survey data is reliable and optimum.
4.2 Results
A one-way between-groups analysis of variance
(ANOVA) was conducted to explore the Saudi
organization's adoption cloud situation of financial
indicators and cloud data center implementation
cost. Table 2 presents comparisons mean value of
financial indicators and cloud data center
implementation cost factors according to
organizations situations of adopting cloud. There
was not a statistically significant difference at the
p<.05 level for the three groups.
Table 1: ANOVA one way test.
Cloud Computing Financial and Cost Analysis: A Case Study of Saudi Government Agencies
463
Regression model in table2 explains the financial
indicators influence the cloud adoption in Saudi
Arabia. Thus, TCO and ongoing support cost
indicators are significant with ROI in cloud
computing adoption decision. According to the
regression results, TCO and ongoing support cost
have a positive linear relationship with ROI.
Table 2: ROI model.
Also, table 3 explains the overall model. Thus,
the overall model for ROI is significant with TCO
and Ongoing Support Cost.
Table 3: ANOVA analysis.
Moreover, regression model in table 4 explains
the implementation cost to adopt cloud in Saudi
Arabia. Thus, data centre variable cost and fixed
costs are significant. Also, they are significant with
TCO financial parameter in cloud computing
adoption. According to the regression results, data
centre variable cost has a positive linear relationship
with TCO.
Table 4: TCO model.
Also, table 5 explains the overall model. Thus, the
overall model for TCO is significant with data centre
variable and fixed cost.
Table 5: ANOVA analysis.
5 DSCUSSION
Peiris et al. (2010) proposed cost equation to
calculate the cloud data centre implementation cost.
They calculated email service cost for the in-house
model and cloud model for the small and medium
organization in Australia. The output from that
calculation used as tipping point parameter to
compare between in-house model and cloud model
cost and to select the best model for the
organization. This paper agrees with previous work
cost equation. But this paper adds value for previous
work by linking the data centre cost to an
appropriate financial indicator (TCO) and represent
this relationship by following equation TCO=
1.156+0.017FC+0.698VC.The earlier study ignored
that. TCO is an important parameter to calculate
direct and indirect costs. This parameter will give
decision makers full vision about a different type of
costs for this solution.
Moreover, the previous work ignored to link data
centre cost to the return on investment (ROI)
financial parameter. This will help decision makers
to decide about their situation to invest in a cloud or
not.
The previous equations can help the organization
to calculate any cloud services cost in both
approaches private and public cloud. If the
organization decide to implement private cloud to
provide any service, then it should be responsible for
the whole cost for different delivery models such as
infrastructure, platform, and software to make this
service workable. However, the cost of
implementing this approach will be high.
However, the cost of public cloud may be cheap,
and the organization can only pay based on its
usability. Also, the previous equation can help to
calculate that cost.
CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science
464
Related to the previous tables, ANOVA one-way
test confirmed there was not a statistically
significant difference between comparisons of
financial indicators and cloud data center
implementation cost factors mean value according to
organizations situations of adopting cloud. Thus, the
participants from different organizations situations
which adopted some cloud services or planned for
the next three years or do not think about cloud
agreed about the financial indicators and cloud data
center implementation play the main role to adopt
cloud. Also, they agreed about financial benefits of
adopting cloud.
The Regression model confirmed the relationship
between financial indicators ROI, TCO and ongoing
support cost to predict the feasibility of cloud
adoption in Saudi Arabia, public organizations. Most
of the participants confirmed that cloud model will
control the expenditures and improve the long return
on investment (ROI).
Also, the regression model confirmed the
relationship between TCO and data center
implementation costs. The data center
implementation cost consist of variable and fixed
cost. Cloud computing model can help the
organization to reduce the implementation cost
(Craig, Frazier et al. 2009, Rastogi 2010, Sharma,
Sharma et al. 2011, Bansal, Sharma et al. 2012,
Rosli, Yeow et al. 2012, Alshomrani and Qamar
2013, Bellamy 2013, Zwattendorfer and Tauber
2013).
The cloud computing facilitates "pay per use"
capability to organizations. This leads to the
organization having the flexibility to use
appropriate bandwidth based on their objectives.
VC and FC play the main role when implementing
cloud data center costs. For example, If VC and FC
are high then that negatively impact on TCO. Thus,
that will also impact negatively on ROI.
6 CONCLUSIONS
It can be concluded that cloud computing technology
has many financial benefits for any organization.
The authors explored a case study from Saudi
government organizations and their experience to
implement cloud to provide their services to their
staff. This paper proposed and validated a financial
model to adopt and implement cloud in Saudi
Arabia. The financial indicators (ROI and TCO) can
help decision makers to measure the cost and
outcome of cloud adoption. This study used
regression method to predict ROI and TCO values.
There is a limitation in this paper. The authors could
not reach to quantitative financial information about
these organizations due to the Saudi government
policy to disclose financial information. Future
works will integrate this model with my previous
models to give the public organizations in Saudi
Arabia comprehensive view to adopt cloud. Also,
more investigation is needed to define cloud system
in Saudi Arabia to contribute more measurements.
REFERENCES
Ahuja, V., J. Yang and R. Shankar (2009). "Benefits of
collaborative ICT adoption for building project
management." Construction Innovation 9(3): 323-340.
Alharbi, F., Atkins, A., & Stanier, C. (2015). Strategic
framework for cloud computing decision-making in
healthcare sector in Saudi Arabia. In "The seventh
international conference on ehealth, telemedicine, and
social medicine "(pp. 138-144).
Alharbi, S. T. (2012). "Users’ acceptance of cloud
computing in Saudi Arabia: an extension of
technology acceptance model." International Journal
of Cloud Applications and Computing (IJCAC) 2(2):
1-11.
Alshamaila, Y., S. Papagiannidis and F. Li (2013). "Cloud
computing adoption by SMEs in the north east of
England: A multi-perspective framework." Journal of
Enterprise Information Management 26(3): 250-275.
Alshomrani, S. and S. Qamar (2013). "Cloud Based E-
Government: Benefits and Challenges." International
Journal of Multidisciplinary Sciences and Engineering
4(6): 1-7.
Amazon (2016). "Amazon elastic compute cloud."
Retrieved 13-09-2016, from http://www.amazon.com/
ec2/
Azure, M. (2016). "Microsoft azure.". Retrieved 15-09-
2016, from http://www.microsoft.com/azure/
Bhisikar, A. (2011). "G-Cloud: New Paradigm Shift for
Online Public Services." International Journal of
Computer Applications 22(8): 24-29.
Borgman, H. P., B. Bahli, H. Heier and F. Schewski
(2013). Cloudrise: exploring cloud computing
adoption and governance with the TOE framework.
System Sciences (HICSS), 2013 46th Hawaii
International Conference on, IEEE.
Chanchary, F. and S. Islam (2011). E-government based
on cloud computing with rational inference agent.
High Capacity Optical Networks and Enabling
Technologies (HONET), 2011, IEEE.
Chang, B.-Y., P. H. Hai, D.-W. Seo, J.-H. Lee and S. H.
Yoon (2013). The determinant of adoption in cloud
computing in Vietnam. Computing, Management and
Telecommunications (ComManTel), 2013
International Conference on, IEEE.
Cloud Computing Financial and Cost Analysis: A Case Study of Saudi Government Agencies
465
Chen, X., G. Wills, L. Gilbert and D. Bacigalupo (2010).
"Using cloud for research: A technical review." JISC
final report.
Depietro, R., E. Wiarda and M. Fleischer (1990). "The
context for change: Organization, technology and
environment." The processes of technological
innovation: 151-175.
Hellerstein, J. M. (2008). Quantitative Data Cleaning for
Large Databases. United Nations Economic
Commission for Europe (UNECE).
IDC. (2016). Retrieved 06-07-2016, from http://idc-
cema.com/eng/trendspotter/63277-ready-for-
digital-disruption-cloud-computing-becomes-
reality-in-saudi-arabia.
Lin, A. and N.-C. Chen (2012). "Cloud computing as an
innovation: Percepetion, attitude, and adoption."
International Journal of Information Management
32(6): 533-540.
Low, C., Y. Chen and M. Wu (2011). "Understanding the
determinants of cloud computing adoption." Industrial
management & data systems 111(7): 1006-1023.
McGeogh, B. T. and B. Donnellan (2013). Factors That
Affect The Adoption Of Cloud Computing For An
Enterprise: A Case Study Of Cloud Adoption Within
Intel Corporation. ECIS.
Mell, P. and T. Grance (2010). "The NIST definition of
cloud computing." Communications of the ACM
53(6): 50.
Misra, S. C. and A. Mondal (2011). "Identification of a
company’s suitability for the adoption of cloud
computing and modelling its corresponding Return on
Investment." Mathematical and Computer Modelling
53(3): 504-521.
Mohammed, F. and O. Ibrahim (2014). "A Survey on
Cloud Government Models.".
Morgan, L. and K. Conboy (2013). "Factors affecting the
adoption of cloud computing: an exploratory study.".
Nkhoma, M. Z., D. P. Dang and A. De Souza-Daw (2013).
Contributing factors of cloud computing adoption: a
technology-organisation-environment framework
approach. Proceedings of the European Conference on
Information Management & Evaluation.
Oliveira, T. and M. F. Martins (2008). A Comparison of
Web Site Adoption in Small and Large Portuguese
Firms. ICE-B, Citeseer.
Peiris, C., B. Balachandran and D. Sharma (2010).
"Governance framework for cloud computing."
Journal on Computing (JoC) 1(1).
Rastogi, A. (2010). "A model based approach to
implement cloud computing in e-Governance."
International Journal of Computer Applications 9(7):
15-18.
Rosli, K., P. H. Yeow and E.-G. Siew (2012). "Factors
influencing audit technology acceptance by audit
firms: A new I-TOE adoption framework." Journal of
Accounting and Auditing: Research & Practice 2012:
1-11.
Saedi, A. and N. A. Iahad (2013). An Integrated
Theoretical Framework for Cloud Computing
Adoption by Small and Medium-Sized Enterprises.
PACIS.
Schubert, L., K. G. Jeffery and B. Neidecker-Lutz (2010).
The Future of Cloud Computing: Opportunities for
European Cloud Computing Beyond 2010:--expert
Group Report, European Commission, Information
Society and Media.
Wen, K.-W. and Y. Chen (2010). "E-business value
creation in Small and Medium Enterprises: a US study
using the TOE framework." International Journal of
Electronic Business 8(1): 80-100.
Yamin, M. (2013). "Cloud Economy of Developing
Countries." World 3(3).
Yesser. (2015). "E-Government Program." Retrieved
15/10, 2015, from www.yesser.gov.sa.
CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science
466