Investigating Cloud Adoption Model using Analytics:

A Case Study of Saudi Government Agencies

Mohammed Mreea, Dharmendra Sharma, Kumudu Munasinghe and Chaminda Hewamaddumage

Faculty of Education, Science,Technology and Mathematics, University of Canberra, ACT, Australia

Keywords: Cloud Computing, Public Organization, Tipping Point, Cloud Factors, Service Delivery Models, Saudi

Arabia.

Abstract: Cloud computing is an innovation in world technology. It is used to provide organization services as a

utility service through the internet and enhance the innovative uptake of cloud computing for improved

effectiveness and efficiency. There are adoption challenges in the uptake of cloud computing by government

agencies. This paper seeks to identify the attributes of cloud computing which are relevant to public

organizations, investigate the factors affecting the adoption of cloud computing and develop an effective

model to address these challenges. Sample government agencies from Saudi Arabia are used to investigate

the challenges and identify the characteristics from which an adoption model is motivated. The proposed

model consists of case study findings based on an analysis of evidence from these organizations. Random

samples from different categories of professionals in Saudi Arabia participated in a questionnaire to extract

and confirm the influential factors from which insights are derived through classification. The results are

then used to determine the tipping point for the uptake of the appropriate cloud model for services provided

by government agencies in the Saudi Arabian context. This paper presents the context, motivations, data

collection approach, analytics on survey results, tipping point parameters and the principle factors for cloud

adoption. Some initial results are presented and future work is summarized.

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. Thus, cloud computing and its elastic

commercial model of information technology (IT)

possession, such as providing data storage and

computing power on mandate, promises to provide

assistance and many rewards for governments and

organizations.

Most of the information technology knowledge

used in cloud computing, such as Web 2.0 and

virtualization, has previously been used

independently. However, cloud computing utilizes

nearly all of these abilities to generate the cloud

computing atmosphere (Schubert, Jeffery et al.

2010). Cloud computing was first proposed in the

1960s (Chen, Wills et al. 2010), when John

McCarthy suggested the idea of using the power of

calculation to deliver utility facilities. While some

attempts to attain this goal have been developed,

such as grid computing, none of them have

prospered in contributing a public provision the way

cloud computing has. Using the cloud frees

administrations from requirements such as needing

to spend money and find a lot of space in order to set

up their organization’s information technology and

permits them to pay capital and fees for only the

facilities they use in their homes or offices. This can

decrease costs and result in both large and small

initiatives saving money. Additionally, cloud

computing gains litheness, giving enterprises a

chance to grow and expand.

However, although there are many benefits of

using cloud computing, it is often necessary to

radically alter organizations’ information technology

infrastructure, procumbent procedures and

management processes in order to obtain these

benefits. Hence, organizations must make significant

changes in their people, IT and procedures to include

Mreea M., Sharma D., Munasinghe K. and Hewamaddumage C.

Investigating Cloud Adoption Model using Analytics: A Case Study of Saudi Government Agencies.

DOI: 10.5220/0006300504490458

In Proceedings of the 7th International Conference on Cloud Computing and Services Science (CLOSER 2017), pages 449-458

ISBN: 978-989-758-243-1

449

cloud computing in their facilities. Cloud computing

systems require important modifications to the group

business model.

This paper will add to academic research by

identifying the challenges in adopting cloud

computing in Saudi Arabia such as availability of

service, effective leadership management, creativity

and a green environment. An in-depth investigation

of these challenges will focus on enhancing the

value proposition for public organizations in Saudi

Arabia to encourage them to adopt this model and

technology.

2 ADVANCES IN CLOUD

COMPUTING

2.1 Cloud Computing

Cloud computing 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 cloud computing facilitates changing

software, 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) defines cloud computing 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 healthcare 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) because it

costs less than traditional infrastructure installations

and allows greater 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). Other

advantages of cloud computing include increased

flexibility, access anywhere, elastic scalability, pay-

as-you-go charging, simplicity and distributed data

centers. Public establishments and administrations

could also benefit from adopting cloud computing

technology; for example, one key benefit for public

facilities is not having the requirement of setting up

their own IT structure and hence reducing costs and

organizational expenses (Bhisikar 2011).

Figure 1: NIST cloud computing concept schema (Alharbi

et al. 2015).

3 INNOVATION ADOPTION

Various research that has been conducted in the

domain of ‘diffusion of innovations’ is

interdisciplinary by nature, involving numerous

areas of science (Rogers 2003). Sociology and

psychology have both been influential on the

innovation and adaptation of the various theories and

models that have been implemented. These two

disciplines concentrate on the behaviour of people

regarding how technology is accepted, while in

information and communication technology (ICT)

the focus is on the features of the system.

Researchers who focus on innovation diffusion have

always been concerned with the acceptance of new

technologies at both organizational and individual

levels.

The diffusion of innovations theory (DIT) has

been exhaustively utilized in studying innovation

adoption and diffusion to explain the policies used

for the adoption of new ideas and technologies by

individuals and organizations. The DIT provides

three attributes of the technology that directly impact

the adoption rate and affect a person’s probability of

adoption or rejection: relative advantage,

compatability and complexity. Relative advantage

measures the degree to which an innovation is

thought to be better than the previous one;

compatibility is expressed as the extent to which a

change is considered to be consistent with the

existing standards; and complexity is the degree to

which an innovation is perceived as relatively

difficult to understand and use.

CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science

450

Tornatzky and Fleischer propose an organization-

level multi-perspective framework known as the

TOE (Depietro, Wiarda et al. 1990). This

framework investigates the impact of three factors

(technology, organization and environment) on the

organization’s decision to adopt a new technology.

The technological level describes the specific factors

that affect an organization’s decision regarding the

adaptation of this technology. The organizational

contexts describe the characteristics of the

organization and the resources that it utilizes. The

environmental context deals with the industrial

domain of the organization and the related factors

such as the potential competitors and technology

service vendors. By integrating DIT and TOE, we

reduce some of the limitations of DOI and can

present a more comprehensive research framework.

3.1 Cloud Computing Adoption

When deciding whether or not to implement cloud

computing in the community sector, the

administration is responsible for calculating the

appropriateness of accepting cloud computing (Lin

and Chen 2012 ,Misra and Mondal 2011). They also

must assess the influence of cloud computing on the

general public and professional processes (McGeogh

and Donnellan 2013) as well as estimate the interior

promptness of the initiative, current IT set-up and IT

human resources for accepting cloud computing

(Low, Chen et al. 2011).

Peiris et al. developed a practical model to adopt

cloud computing in a private organization in

Australia. This model is called the cloud computing

tipping model (Peiris et al. 2010). Their model can

be used by companies to determine whether

adopting cloud computing is beneficial to them or

not. This provides an in-depth investigation from the

business and technical perspectives. This model uses

proven industry practices such as COBIT (Control

Objectives for the Information and related

Technology) to identify the important attributes that

impact ICT organizations in Australia when

adopting this technology. These attributes are

efficiency gains and a resulting increase in

competitive advantages, better creativity, and

innovation in products and customer services,

improved agility, better security and risk

management, better socialization among employees

and improved simplicity of IT systems. That model

was implemented as artfact and simulated by

experiments.

Oliveira and Martins use the TOE model to

identify a set of determinants of the adoption of

cloud computing by firms (Oliveira and Martins

2008). Their study is theoretically rather than

empirically tested and a primary model is suggested

based on conceptual reasoning and the literature

review. The main factors that the study discusses are

size, top management support, global scope,

technological readiness, competitive pressure and

regulatory support. Low et al. (2011) investigated

the factors that affect the adoption of cloud

computing by firms in the high-tech industry in

Taiwan. They used the TOE model to examine these

factors via a questionnaire-based survey used to

collect data from 111 companies. They found

competitive pressure, trading partner pressure,

relative advantage, top management support, and

firm size characteristics have a significant impact on

the adoption of cloud computing. Lin and Chen

(2012) investigated the critical factors that affected

the decision to adopt cloud computing technology in

Taiwan’s hospital industry. They designed a

questionnaire based on the TOE model for the chief

informational officers (CIOs) in Taiwan’s hospitals.

Their results indicated that the significant factors

concerning the adoption of cloud computing are

cost, top manager support, complexity, data security,

and technical competence.

Nkhoma et al. (2013) also used the TOE model to

find the adoption decision drivers in order to create

opportunities for future cloud technologies to be

aligned with consumers’ needs (Nkhoma, Dang et al.

2013). Chang et al. used the TOE framework to

study the adoption of cloud computing in

Vietnamese companies (Chang, Hai et al. 2013). The

level of cloud computing adoption in Vietnam is in

the foundation stage because there are not many

adopters. The study identified eight factors as

determinants of cloud computing adoption:

technological complexity, relative advantage,

trading partners’ pressure, top management support,

formalization, IT infrastructure availability,

organizational size and competitive pressure.

Borgman et al. (2013) used the TOE model to

investigate the factors that affect the decision to

adopt cloud computing (Borgman, Bahli et al. 2013).

They developed a set of hypotheses that were tested

in a quantitative study of 24 international enterprises

across various industries. They found that

organizational and technological factors affect

implementation decisions. This literature review

demonstrates that there is no existing model that

public organizations can use to help decision-makers

Investigating Cloud Adoption Model using Analytics: A Case Study of Saudi Government Agencies

451

conduct an in-depth evaluation to investigate the

main attributes which affect their decision to accept

cloud adoption.

3.2 Cloud Computing Adoption in

Saudi Government

According to the International Data Corporation

(2016), Saudi Arabian individuals and private and

small organizations invested about US$ 50.4 million

on cloud services in 2014 and they expected this

figure to reach US$ 77.4 million in 2016. Most of

their requirements were email, communication and

collaboration, and content management. However,

Saudi government entities are the biggest resistors to

adopting cloud computing (IDC 2016) and 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. A

major push and initiative from someone in a position

of authority or a member of the royal family is

needed before the Saudi government will develop a

strategy to discover the essential benefits offered by

cloud computing solutions to stakeholders. Other

reasons for this resistance are a lack of awareness

and security issues.

In Saudi Arabia, cloud computing is still in its

beginning stages. Few studies have been conducted

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.

Additionally, 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) did a study of cloud computing awareness

from an organization level in Saudi Arabia. He

predicted that cloud computing will be a future

platform for Saudi’s organizations. Alkahter (2014)

identified 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 and

privacy had a significant impact on the decision to

adopt cloud computing.

Reviewing the previous studies illustrates that

there is an absence of theoretical and empirical

studies concerning the adoption of cloud computing

in the government sector in developing countries,

specifically in Saudi Arabia. Public organizations’

business initiatives are different and more complex

than those of a private organization. Researchers

have emphasized the need for an increased focus on

how organizations adopt innovations (Mohammed

and Ibrahim 2014). Some researchers recommend

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 data on government

adoption in order to determine the tipping point

parameters and principle factors. Thus, providing

more data analytics is a valuable contribute to the

research.

3.3 Proposed Cloud Computing

Adoption Model for Saudi

Government

The authors address the need to find the main factors

which impact on an organization adopting cloud

computing and conclude the main tipping point

parameters based on survey analyses. The author

conducted two cases studies of participants’ who

responded to the survey to clarify their responses.

3.3.1 Case Study 1

The first case study analysed a Saudi government

organization regarding their adoption of cloud

services. This organization is a part of the education

and training sector in Saudi Arabia. They have

recently implemented the Google cloud email

service package of Google Apps Suite. This

organization manages about 32 faculties across the

Kingdom of Saudi Arabia and they employ more

than 1,000 staff. IT lecturer who held a senior IT

position in this organization’s data center had been

interviewed to clarify his survey responses. He told

me about the obstacles in providing email services to

all the staff in this organization. The main obstacle

was availability, in that they could not guarantee the

availability of the email service and, when it did not

work, this service stayed offline for a long time until

they fixed it. This occurred because the organization

CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science

452

had no qualified people to manage it, a shortage in

support contracts and a lack of financial resources.

On occasion they had asked academic IT staff to

work with them as IT support staff.

Other issues faced by the organization included

security patches and limitations in storage. Finally,

they faced a problem with data center space and the

growth in some 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 growing demand

from the organizational staff for email services, the

organization adopted cloud computing in order to

provide this service to its employees. After adopting

the email service via the cloud, they noted the

difference between in-house email and cloud email.

They achieved many benefits, such as improved

efficiency in their services, 24x7 availability,

increased mailbox size and good security

management with advanced hardware. They also

gained good support via qualified people from the

provider, which saved the organization space that it

could use as training centers for students.

Maintenance and development costs decreased.

Also, transferring what had been a problem to

qualified providers simplified their business model.

Finally, by reducing the number of servers, the

organization contributed to a cleaner environment.

3.3.2 Case Study 2

The second case study analysed a different Saudi

government organization regarding their adoption of

cloud services. This organization is a part of the

military sector in Saudi Arabia that recently

implemented a private cloud model to provide some

services for its staff such as email services. These

organizations manage over 25 branches across the

Kingdom of Saudi Arabia. They have more than

2500 staff. IT manager in this organization had been

interviewed to clarify his survey responses. He

described why the organization decided to adopt

some cloud services such as email and SharePoint.

The reasons that motivated the organization to adopt

cloud services were the growth in the number of

branches as well as human resources and the

organization’s objectives. If they went with

traditional in-house IT services, they would need to

create a complete infrastructure for every branch

with software licences and the cost would have been

high. Thus, cost saving is important for them

because they have limitations in their budget.

Additionally, security is important for them because

they deal with a lot of sensitive data. Thus, they

implemented a private cloud infrastructure at head

office. He reported that while this type of model is

costly and more complex to manage than a public

cloud deployment model, for his organization,

security issues have the highest priority.

The outcomes of adopting the cloud for this

government agency were improved user

collaboration and productivity, service availability

anywhere and anytime for their staff, cost savings

relative to a decentralized model, improved power

consumption and increased efficiency and

effectiveness of the technology and workforce.

3.3.3 Analysis of Case Studies

3.3.3.1 Case Study 1

A close look at Case Study 1 reveals that the

decision to adopt Google’s cloud computing services

through the provider was a result of organizational

changes. This decision helped the organization face

growth challenges as well as to fix the issue of

existing resource capabilities, such as using

lecturers as support staff, which had impacted

negatively on the organization’s objectives.

The key points that can be understood from this

case study are the following:

1. Cloud computing can provide more

availability and reliability for

organizational services. Thus, availability

is one of key tipping point parameters for

adopting cloud computing.

2. Cloud computing can provide more

flexibility and agility by responding

quickly to a growth in users or new

organizational requirements. Thus,

flexibility and agility are two of the key

tipping point parameters to adopt cloud

computing.

3. Cloud computing helps organizations to

be greener by saving data center space

and power consumption. Thus,

supporting a green environment is one of

the critical tipping point parameters to

adopt cloud computing.

4. Cloud computing can help with resource

capabilities. Thus, an adequate resource

capability is a factor that positively

influences the adoption of cloud

computing.

5. Cloud computing can help to decrease

variable and fixed infrastructure costs

significantly.

Investigating Cloud Adoption Model using Analytics: A Case Study of Saudi Government Agencies

453

6. Cloud computing will improve

competitive advantages and efficiency by

increasing the focus on core

competencies and objectives because

some of the IT services have been

outsourced to a service provider.

7. Cloud computing is an optimal option

when an organization has limited funds.

8. Cloud computing as IT innovation

technology works as the best enabler for

Case Study 1 to focus on core business

objectives.

9. The growth in organization size and

effective leadership support played a

main role in this case in the decision to

adopt cloud computing. Thus, effective

leadership is a positive influence on the

adoption of cloud computing.

10. Finally, simplicity played a main role in

the decision to adopt Google Apps Suite

in this case.

3.3.3.2 Case Study 2

A close look at Case Study 2, a government

organization in the military sector, reveals that the

decision to adopt and implement private cloud

computing was a result of major organizational and

business objective changes and an expansion that

created new branches throughout Saudi Arabia.

They took the action to adopt their own cloud to

manage and provide necessary IT services such as

email and SharePoint through the head office. They

agreed that the implementation of a private cloud

deployment model is costly, but they prefer it for

security concerns. Security is the highest priority for

them over other factors such as cost.

The key points that can be understood from this

case study are the following:

1- Cloud security is a significant matter for

this organization’s business requirement.

2- The military sector of public organizations

pays more attention to security than other

benefits.

3- Cloud computing technology is flexible

technology that can provide multiple types

of deployment models based on the

organization’s needs.

4- The complexity of deploying and

managing a private cloud model was a

negative influence on this case.

5- The cloud increases the efficiency and

effectiveness of the technology and

workforce.

6- Cloud computing can provide major

socialization among an organization’s

staff as they can become nearer in

effective association regardless of their

physical location.

3.3.4 Proposed Adoption Model

Based on the challenges identified in the above case

study analysis, Figure 2 shows a proposed TOE

model.

Figure 2: Proposed model.

4 VALIDATING THE CASE

STUDIES FINDINGS

The authors continued to validate the proposed

model which was generated by previous case

studies. They have investigated several research

methods to complete this task. They decided the

survey method is a good instrument to achieve

suitable outcomes. They produced a comprehensive

survey based on previous studies which used the

TOE framework and a cloud computing tipping

point study (Peiris et al 2010). This survey was

distributed to decision-makers, information

technology (IT) managers and experts at government

organizations in Saudi Arabia to explore their

experience with cloud computing interaction through

a series of questions. Most of the participants in this

survey held senior IT department and IT

CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science

454

management positions, so they therefore had the

capability to recognize the future trends and current

situation of their organizations.

About 102 participants responded to this survey.

Their data helped to determine the decision-makers’

perceptions of cloud computing platforms as

opposed to an in-house platform. Additionally, the

responses allowed the researchers to find effective

response models for their challenges.

The survey used a five-point Likert scale to

gather participant’s inputs, which ranged from 1

(strongly disagree) to 1 (strongly agree). The survey

consists of 46 questions. The collected data was

analysed by SPSS and R software.

5 DATA RESULTS AND

ANALYSIS

5.1 Data Analysis

The data used in this project was collected through a

survey conducted in Saudi Arabia. The participants

in the survey belonged to different organizations and

work in different professional categories. All of the

collected data are in categorical measurements. The

aim of this analysis is to clarify the previously

developed models for cloud computing in Saudi

Arabia. The cluster analysis method was used to

identify the similarities and dissimilarities in the

cluster model for cloud computing. Before starting

the analysis process, we did data cleaning to get a

clear dataset on behalf of optimum analytical results.

In data cleaning, we removed the out of range and

duplicated data.

5.1.1 Data Cleaning

Data cleaning is an important step before analysing

data. Data cleaning is process of removing irrelevant

information, removing out of range data, and

removing incorrect answers from a questionnaire.

This procedure is especially necessary for survey

data. Survey data has a lot of irrelevant information,

out of range information and incorrect answers to

questions. Data cleaning is a useful step to get rid of

analytical errors. Incorrect information leads to

incorrect decisions and incorrect conclusions, so it is

an important step to clean the data before analysis.

Errors of data can happen for many reasons and

some of the different ways that data errors can

happen is explained below (Hellerstein 2008).

If the dataset is comparatively small, a manual

data cleaning method can be applied. In this process,

data sorting is a required step. When data has been

sorted it is easy to identify irrelevant data from the

spreadsheet. However, most datasets have millions

of records and a vast numbers of attributes. In this

situation, manual data cleaning methods are not

possible, so computer base algorithms can be used to

clean data.

5.1.2 Analytical Methods

Data distribution was not clearly satisfied with

normal distribution assumptions. Both kurtosis and

skew were not zero (Mordkoff 2011). Cluster

analysis and regression analysis are used to identify

the tipping points in the survey results. Cluster

analysis divides the data into meaningful groups.

Regression analysis is used to identify the significant

individual variables and regression analysis explains

the overall significance of the model.

5.2 Results

The cluster model and regression models were used

to identify the participants’ preferences concerning

the implementation of cloud computing in Saudi

Arabia. Figure 3 explains five clusters according to

the participants. Participants in each cluster had

similarities about their preferences of cloud

computing. According to the organization type,

situation and participants’ position, the organization

had similar ideas about the implementation of cloud

computing. The first cluster on the left side

represents 28% of civil organization employees who

held IT manager positions. 22% of them have a plan

to adopt cloud computing in next three years and 6%

reported that they did not think about the cloud. The

second cluster represents 35% of civil organization

employees who held CIO, senior manager and

computer engineer positions. All of them planned to

adopt cloud computing in the next three years. The

third cluster represents 10% of military organization

employees who have IT architect, senior manager

and policymaker positions. 7% of them adopted

some cloud service and the other in next three years.

Cluster 4 represents 12% of civil organization

employees who have CIO and senior manager

positions. All of them adopted some cloud services.

The last cluster represents 11% of civil organization

employees who have IT manager and IT architect

positions. They reported adopting some cloud

services.

Investigating Cloud Adoption Model using Analytics: A Case Study of Saudi Government Agencies

455

These results show that participants from IT-

related organizations have positive ideas about cloud

computing. However, the participants from non-IT

organizations had different ideas about cloud

computing.

Figure 3: Cluster diagram (1).

According to the Figure 4 cluster diagram,

participant numbers 5, 11, 16, 30, 56 have similar

ideas about cloud computing. All of these

participants are in same organizational situation and

hold similar position types. All of those participants

are IT professionals and they are interested in cloud

computing. The other four clusters have overlapping

participants. There are no significant dissimilarities

among those clusters.

Figure 4: Cluster diagram (2).

The regression model was used as an effective

model to respond to challenges in cloud computing

adoption in Saudi Arabia. One of the organizational

challenges for the adoption of cloud computing in

Saudi Arabia is leadership support. Thus, the model

in Table 1 explains the factors influencing this

challenge. Organization size, social impact,

creativity, being green, resource capability and

security factors are significant parts of the leadership

challenge to adopt and implement cloud computing.

According to the regression results, creativity and

going green a have positive linear relationship with

dependent variable (leadership support) while

resource capability has a negative linear relationship.

The relationship between leadership (dependent

variable) and other predictors’ variables can be

represented by the following equation:

Table 1: Regression model for organizational challenges.

Table 2 explains the overall model. Thus, the

overall model for leadership support is significant.

Table 2: ANOVA Regression model.

Additionally, the regression model in Table 3

explains that the availability of services is a

challenge to adopting and implementing cloud

computing in Saudi Arabia. Thus, simplicity,

compatibility, efficiency and security parameters are

significant. According to the regression results,

efficiency and security have a positive linear

relationship with availability. The relationship

between availability (dependent variable) and other

predictors’ variables can be represented by

following equation:

Table 3: Regression model for technological challenges.

CLOSER 2017 - 7th International Conference on Cloud Computing and Services Science

456

Table 4 explains the overall model. Thus, the

overall model for availability is significant with

efficiency and security.

Table 4: ANOVA Regression model.

6 DISCUSSION

Based on the participants’ data and cluster algorithm

results, we found a relationship between the

participants’ knowledge and experience and their

acceptance towards adopting cloud computing.

People with IT qualifications are more confident

with cloud technology than people without these

qualifications. Coursaris and Kim (2011) found that

adoption can be influenced by four sets of contextual

factors: technology, user, environment and tasks.

Thus, knowledge and experience can be considered

two of the main contextual factors that promote or

hinder the adoption of cloud computing in Saudi

government organizations. Government policies can

also play a main role in accepting cloud adoption.

However, to date there are no specific policies set by

the Saudi government regarding the adoption of

cloud computing.

The regression model provided an effective

model for some challenges which impact on the

cloud adoption and implementation decision. The

availability of services plays a main role in cloud

computing adoption. Thus, it can be assumed that

the availability of services is a tipping point

parameter to the adoption of cloud computing in

Saudi Arabia. Also, to guarantee good availability of

services, there needs to be a secure, efficient,

manageable and compatible platform to implement

it. Security is a highly significant parameter for

availability.

Additionally, leadership support plays a main role

in adopting cloud computing. Thus, it can be

assumed that leadership support is a tipping point

parameter to adopt cloud computing in Saudi

Arabia. This parameter depends on organization

size, social impact, creativity, going green, adequate

resource capability, and security. Top management

people think about environmental benefits, thus

going green represents being environmentally

friendly. This factor is highly significant and

impacted on leadership support towards adopting

cloud computer. Finally, these results agreed with

some previous studies such as Peiris et al (2010)

concerning social impact and security parameters.

7 CONCLUSIONS

It can be concluded that cloud computing technology

has many benefits for any organization. Government

agencies are looking for innovative technology for

their services and the cloud can be the right

innovative technology for them. The authors

explored two case studies from Saudi government

organizations and the experience of staff within

those organizations concerning implementing cloud

computing to provide services to their staff. This

paper found a positive perception from civil

organizations toward adopting a cloud platform.

Also, it identified new challenges such as

availability, leadership support and green

environment. Effective models contribute to

overcoming availability and top leadership support

challenges.

It can be concluded that knowledge and

experience are the main contextual factors that can

speed up the adoption of technology. Finally, we can

conclude that most of the top level professionals in

public organizations in Saudi Arabia are interested

in cloud computing technology. Future works will

investigate the model data in-depth to figure out the

impact of these results.

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

Investigating Cloud Adoption Model using Analytics: A Case Study of Saudi Government Agencies

457

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.

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.

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

458