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Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
SCIENCE & TECHNOLOGY
Journal homepage: http://www.pertanika.upm.edu.my/
Article history:
Received: 4 August 2021
Accepted: 29 September 2021
Published: 10 January 2022
ARTICLE INFO
E-mail addresses:
mosama@graduate.utm.my (Osama Abied)
othmanibrahim@utm.my (Othman Ibrahim)
sitin509@uitm.edu.my (Siti Nuur-Ila Mat Kamal)
*Corresponding author
ISSN: 0128-7680
e-ISSN: 2231-8526 © Universiti Putra Malaysia Press
DOI: https://doi.org/10.47836/pjst.30.1.36
Review Article
Adoption of Cloud Computing in E-Government: A Systematic
Literature Review
Osama Abied1*, Othman Ibrahim1 and Siti Nuur-Ila Mat Kamal2
1Department of Information Systems, Azman Hashim International Business School, Universiti Teknologi
Malaysia, 81310 Skudai, Johor, Malaysia
2Faculty of Information Management,Universiti Teknologi MARA, Jalan Universiti O KM 12 Jalan Muar,
85000 Segamat, Johor
ABSTRACT
Cloud computing in governments has become an attraction to help enhance service delivery.
Improving service delivery, productivity, transparency, and reducing costs necessitates
governments to use cloud services. Since the publication of a review paper on cloud
adoption elements in e-governments in 2015, cloud computing in governments has evolved
into discussions of cloud service adoption factors. This paper concentrates on the adoption
of cloud computing in governments, the benets, models, and methodologies utilized,
and the analysis techniques. Studies from 2010 up to 2020 have been investigated for this
paper. This study has critically peer-reviewed articles that concentrate on cloud computing
for electronic governments (e-Governments). It exhibits a systematic evaluation of the
empirical studies focusing on cloud adoption studies in e-governments. This review work
further categorizes the articles and exhibits novel research opportunities from the themes
and unexhausted areas of these articles. From the reviewed articles, it has been observed
that most of the articles have employed the quantitative approach, with few utilizing
qualitative and mixed-method approaches. The results reveal that cloud computing adoption
could help solve problems in learning, such
as infrastructure issues, cost issues, and
improve service delivery and transparency.
This review gives more information on
the future directions and areas that need
attention, like the trust of cloud computing
in e-governments.
Keywords: Adoption, cloud computing, cloud
services, e-government
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INTRODUCTION
As Information Technology innovation is advancing (Sallehudin et al., 2020), cloud
computing in governments is helping improve productivity (Ali et al., 2018b) while
enhancing efficiency, transparency, and public service delivery (Mohammed et al.,
2016; Nanos et al., 2019). Furthermore, since the evolution of cloud computing in the
2000s (Bayramusta & Nasir, 2016; Senyo et al., 2018), there have been developments
in the automation of existing procedures, making infrastructure, software, and platforms
easily available on-demand for pay (Sharma et al., 2020). Recently, cloud computing has
become a strategic direction for e-governments around the globe because of its benet
in overcoming infrastructure issues as well as attaining cost reduction (Mohammed et al.,
2020; Singh et al., 2020).
Cloud computing has also attracted several studies (Senyo et al., 2018). There is no
doubt that various large governmental organizations are using cloud computing dierently.
Apart from becoming popular, it has become a powerful driver for economic and
technological changes worldwide (Vu et al., 2020). For instance, in healthcare predictions
(Anuradha et al., 2021; Tuli et al., 2020), in smart cities (Wang et al., 2020), in small and
medium enterprises (Alismaili et al., 2020), in governments (Zhang, 2020), and education
(Vaidya et al., 2020), among other elds. Moreover, the utilization of cloud computing
has yielded unprecedented opportunities for organizations to improve their performance.
Besides this, the unique properties of cloud computing have made modern governments
transparent, ecient, eective in response, and creative (Al Mudawi et al., 2019; Ali et
al., 2018a; Nanos et al., 2019).
Hence, with this trend, utilizing cloud computing will create convenience, improve
accessibility and quality of delivery of government services, and improve the flow
of information and procedures. It will further improve the speed, coordination, and
enforcement of activities in the public sector. This paper focuses on existing literature
on cloud computing as a supporting technology for e-governments and brings out the
themes, methodologies, trends, critical factors, theories, and data analysis techniques
in past studies. This paper will critically evaluate existing works and studies on cloud
computing in e-governments and highlight new research areas. Three research questions
have been developed as explained subsequently to guide this study. The systematic review is
complementary to the past studies and gives the following contributions for the researchers
interested in cloud computing and e-governments to further their studies. The following
research questions will guide this study:
RQ1. What is the research area in focus in cloud computing on e-governments?
RQ2. How is cloud computing used to improve service delivery in e-governments
(benets)?
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Cloud Computing in E-Government
RQ3. What themes, factors, methods, level of implementation, data analysis
techniques, and methodologies are available, and what is the gap for cloud computing
in e-governments?
The research identies primary studies related to cloud computing in e-governments
from 2010 to 2020. Other researchers can utilize this list to further their work. The research
further selects studies that meet the criteria set for quality assessment. These studies are
a good ground for comparing similar works. Comprehensively, this study analyzes the
articles and brings out the ideas, themes, methods, methodologies, level of implementation,
and factors in the eld of cloud computing and e-governments. Finally, a discussion is
presented on how to further this work.
This paper is outlined as follows: Section 3 examines the methods used in this study
and the primary studies that were systematically chosen for evaluation. Section 4 discusses
the ndings from the primary studies. Section 5 carries out a discussion as highlighted
in the research questions. Lastly, section 6 presents the conclusion and suggestions for
further research.
PRIOR RESEARCH
Specically, and to the best of the researchers’ knowledge during this research, the
systematic literature reviews (SLRs) concerning the application of cloud computing in
e-governments are still limited in number. One of the most recent surveys was on the
eect of cloud computing on the sustainability of government services (Mohammed et
al., 2020). In this study, the authors identify the gap in incorporating cloud computing as
a platform for establishing sustainable services. In the view of this study, the researchers
give an important starting point to fellow researchers interested in cloud computing in
e-governments. Apart from this, several studies about cloud computing and its extensive
use have also been published, and this study will examine them consecutively to extract
their dierences in the themes chosen by the authors and this research.
A systematic review was done on cloud computing and e-governments (Tsaravas
& Themistocleous, 2011). The study highlights the application of Service-Oriented
Architecture in e-governments and the utilization of cloud computing in the public sector.
In addition, the study highlights the benets and obstacles of cloud computing, the service
models used in cloud computing, and the deployment models. The study also examines
the case studies in the cloud in e-governments. However, the study excludes the models,
methodologies, level of implementation, themes, and critical factors and focuses mostly on
the government organizations in some cities that have adopted cloud computing solutions
for improved service delivery.
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In 2015, a review was conducted on models of adopting cloud computing in an
e-government context (Mohammed & Ibrahim, 2015a). Interestingly the paper highlights
the benets and challenges of cloud computing in e-government structures and examines
the proposed cloud computing adoption models. Furthermore, it classies the models
into various categories, such as “layered-based,” “step-based,” “component-based,”
and “conceptual/theoretical” models. Since 2016 the application and adoption of
cloud computing have grown, and as such, our research seeks to bring out the themes,
methodologies, level of implementation, data analysis techniques, and critical factors that
have been examined.
A systematic review was also conducted on factors aecting the adoption of cloud
computing in e-governments (Wahsh & Dhillon, 2015b). The paper concentrates on the
factors aecting cloud adoption in e-governments for public sectors, and this research
covers a timeline of up to 2015. The paper suggests an extension of research to include
theoretical models. Therefore, our research will seek to highlight the models and factors that
have been brought out till 2020. The themes, the level of implementation, methodologies,
and data analysis techniques will also be highlighted.
All the past studies mentioned above highlight the wider use of cloud computing;
however, they leave out some elements like the methodologies, the level of implementation,
data analysis techniques, the factors, and themes used for better adoption solutions.
Furthermore, the eld of cloud computing in e-governments is growing relatively fast.
Hence, it is of signicance to provide a summary of the upcoming research studies, more
so in cloud computing in e-governments, to act as a guideline for new research studies.
RESEARCH METHODOLOGY
This study conducted a systematic review with the guidance of Kitchenham and Charters
(Kitchenham & Charters, 2007) to answer the research questions. The study goes through
the planning, execution, and reporting stages of the review while revisiting them back and
forth for a thorough examination of the systematic review.
Choosing Primary Studies
The primary studies were selected based on keywords via the search engine or search facility
of the journal. The platforms under investigation included IEEE Xplore digital library, Wiley
Online, Library, SpringerLink, Google Scholar, ScienceDirect, ACM Digital Library, and
Scopus. The exploration was done using the keywords, title, or abstract grounded on each
specic platform. The keywords were chosen to enhance the appearance of the study results
that would help answer the research questions. The Boolean operators “AND” and “OR”
were used where relevant. The search strings used were: (“cloud computing” OR “cloud-
computing” OR “cloud service” OR “cloud adoption” OR “cloud implementation”) AND
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Cloud Computing in E-Government
(“e-government”), and (“cloud computing” OR “cloud-computing” OR “cloud service”
OR “cloud adoption” OR “cloud implementation”) AND (“public service” OR “public
sector” OR “public service delivery”).
The investigation included any study published from 2010 up to 2020 December. The
outcomes were ltered via the inclusion/exclusion measures as presented. The measures
enabled the production of outcomes that underwent snowballing from the explanation
given (Wohlin, 2014). This study conducted backward and forward snowballing until the
inclusion measures were attained.
Inclusion and Exclusion Measures
This section describes the inclusion and exclusion measures considered while ltering
the study search results for this research. Any literature chosen for this SLR must have
given empirical outcomes and should have carried out the study via case research, new
technical cloud computing utilization, and commentaries on establishing e-governments
through cloud service applications. The research articles should have been peer-reviewed
and documented in English. The outcomes from Google Scholar were scrutinized for
compliance with the measures as chances could arise for Google Scholar to furnish papers,
which are graded lower. The current researched versions were also included in this study.
The inclusion and exclusion measures are detailed in Table 1.
Table 1
Inclusion and exclusion criteria
The article must have details linked to cloud
computing or associated with cloud service
technologies in e-government
Articles concentrating on the impact of
cloud computing in e-government or public
sector
The article must present empirical data
linked with the adoption and application of
cloud computing in e-government
Grey information like blogs and government
documents
The article must be in English, peer-
reviewed, and published in a journal or
conference proceeding from 2010 to 2020
Non-English articles, outside the year range
Selection Outcomes
There were up to 654 studies identied from the initial keyword search on the selected
platforms. It was reduced further using the inclusion and exclusion criteria and after
removing a lot of duplicate studies. The number of papers that were read in full was 94
papers. The 94 articles were then fully read using the inclusion and exclusion criteria, and
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Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
20 papers remained. Applying forward and backward snowballing established eight papers,
giving an ultimate gure of 28 papers to be included in this SLR.
Quality Assessment
Evaluation of the quality of the primary research articles was undertaken by following
the direction of Kitchenham and Charters (Kitchenham & Charters, 2007). Accordingly,
the evaluation was done to extract the relevant articles connected to the research inquiries
without any biases and with the validity of the empirical data. The evaluation procedure
is grounded on previous research by Hosseini et al. (2017). Five randomly chosen articles
were put through the quality evaluation procedure to examine their eciency. The procedure
is as follows:
Step 1: Cloud computing. The article must concentrate on adopting cloud computing
or the application of cloud service to a specic, well-mentioned issue.
Step 2: Context. The required context must be given for the study’s aim and outcomes.
It permits good result interpretation.
Step 3: Cloud computing application. The article must possess the right information for
a perfect exhibition concerning the utilization of innovation for a particular problem.
It aims to answer RQ1 and RQ2.
Step 4: E-government context. The article must furnish information about the
e-government problem to attempt and answer RQ3.
Step 5: Cloud computing performance. It seeks to evaluate cloud service performance
in e-government. It will help bring benets for cloud services.
Step 6: Data gathering. Information about models/frameworks, data collection,
measurement, and presentation must be included for precision.
The checklist mentioned above for quality estimation was utilized for every other
primary article chosen.
Data Extraction
Every paper that successfully went through quality evaluation underwent data extraction to
examine the fullness of data to validate the accuracy of the details gathered in the articles.
Data extraction was rst done on the rst ve articles before expansion to incorporate
all the articles that successfully underwent the quality evaluation stage. Then, extraction,
grouping, and caching of the information were done using excel spreadsheets. The
groupings entailed: context details or theme (detailing purpose of the study), methodology
(qualitative or quantitative data), level of implementation (organizational or individual),
factors (signicant elements for adoption), framework or model (information system
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models), and data analysis methods (PLS/SEM). Figure 1 exhibits the articles chosen
at every phase of the procedure and the rate of every article selected from the keywords
utilized in the search to the ultimate choice of the primary articles.
ANALYSIS AND FINDINGS
The details were compiled within the qualitative and quantitative data groups to answer
the research questions. The study also did a meta-analysis of the articles that went to the
nal extraction procedure. The results are subsequently discussed.
Publication Rate
The concept of cloud computing was started as early as 1961 by John McCarthy, but its
usage by organizations only began in 2009 (Attaran & Woods, 2018). Hence, this study
nds no nal primary studies with empirical results published before 2015. It shows that
the idea is not fully saturated for e-governments. Figure 2 shows the number of primary
studies published every year.
Figure 1. Extraction of the articles through the process
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Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
As can be seen from Figure 2, the trend is not consistent, but there were more
publications in 2017 compared to all the other years. This study forecasts that there are still
many studies coming up on cloud computing in e-governments. The number of publications
in 2019 was very low compared to the other years.
Figure 2. Primary studies published overtime
However, from Figure 2, 2020 has shown an upward trend in the usage of cloud services
in e-governments compared to 2019, which received only a few studies. Information and
communication technologies still play a role in good governance and public service
delivery; hence, the researchers anticipate seeing more studies as years go by.
The Eect of Keyword Counts
To summarize the common themes in the chosen primary studies, 28 articles were analyzed.
Figure 3 shows the word cloud from the 28 studies utilized in this paper.
Furthermore, Table 2 exhibits the number of times specic words were seen in the
primary studies.
The analysis of keywords was performed across all the 28 primary studies to summarize
the common themes in the primary studies. Table 2 exhibits the number of times specic
words appeared in all the primary articles. From Table 2, excluding the keywords that
were chosen for this study, which were “cloud computing” and “e-government,” the third
keyword that appears most frequently is “adoption,” followed by “information,” and then
“model.” It shows an interesting trend in the adoption of cloud computing. Adoption is the
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Cloud Computing in E-Government
Figure 3. Shows the word cloud
Table 2
Word count for the primary studies
Word Length Count Weighted
Percentage
cloud 54128 2.45%
government 10 2399 1.42%
adoption 82076 1.23%
computing 92034 1.21%
information 11 1313 0.78%
technology 10 1085 0.64%
services 8863 0.51%
public 6850 0.50%
study 5816 0.48%
factors 7804 0.48%
research 8782 0.46%
model 5779 0.46%
management 10 769 0.46%
journal 7622 0.37%
service 7605 0.36%
systems 7558 0.33%
based 5536 0.32%
innovation 10 524 0.31%
perceived 9479 0.28%
security 8461 0.27%
Table 2 (Continue)
Word Length Count Weighted
Percentage
organization 12 458 0.27%
decision 8417 0.25%
international 13 412 0.24%
trust 5403 0.24%
using 5391 0.23%
business 8379 0.22%
organizational 14 372 0.22%
system 6350 0.21%
results 7331 0.20%
organizations 13 330 0.20%
value 5328 0.19%
support 7322 0.19%
intention 9319 0.19%
adopt 5316 0.19%
theory 6302 0.18%
users 5302 0.18%
table 5298 0.18%
eect 6297 0.18%
studies 7293 0.17%
inuence 9292 0.17%
sector 6286 0.17%
technological 13 286 0.17%
analysis 8279 0.17%
acceptance 10 274 0.16%
usage 5271 0.16%
resources 9267 0.16%
signicant 11 266 0.16%
implementation 14 260 0.15%
process 7258 0.15%
important 9256 0.15%
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word mentioned most, and in relation to Figure 2, more adoption studies were conducted
in 2018. A uctuation of studies conducted yearly has been observed. Moreover, 2020 has
seen a tremendous rise in the adoption of cloud services. Adoption is further highlighted
in the discussion section.
Every primary article extracted was read in full, and the qualitative and quantitative
details were captured, along with the data analysis technique used, the themes, factors,
and the respondents for the study (Appendix A).
All the studies focused on the adoption or usage and factors for the adoption of cloud
computing in e-governments. Moreover, some studies mentioned the benets of the cloud
in e-governments, the cloud service models that can be used, as well as the deployment
models. Few studies also highlighted the barriers to cloud adoption. Within the extracted
papers, some authors also highlighted the benets of cloud computing in e-governments.
This study also extracted the methodologies that every paper has adopted. Figure 3 shows
the distribution of the methodologies adopted by the dierent studies.
Figure 4. Research methodologies used in the primary studies
According to Figure 2, most studies have used the quantitative method, while very few
studies have adopted the mixed method. The information was extracted from the primary
studies, and it details the methods used, as shown in Appendix A. While most studies have
highlighted the factors for the adoption of cloud computing with models/theories, this
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research still highlights that TOE is the most used model for studying cloud adoption in
e-governments (13 studies), while DOI (12 studies) follows closely (Appendix A). TOE is
a model established to examine technology adoption at the organizational level (Tornatzky
et al., 1990). Accordingly, most studies use TOE to study adoption behavior and a holistic
approach (Al Hadwer et al., 2021; Alkhalil et al., 2017; Awa et al., 2017). For governments
to deliver online services, TOE is appropriate as it helps to investigate the adoption factors
for cloud computing in governments (Hsu et al., 2014). It is also a holistic instrument for
organization-level studies.
Similarly, DOI has been used by most studies for the adoption and diusion of
innovations, as shown in this study (Appendix A). According to Rogers, this theory can
predict the decisions of people in the adoption of new technologies through the examination
of patterns and structure (Rogers, 2010). The theory examines adoption through the features
of innovation. Furthermore, the model points to the need for exposure to the innovation
when the adoption process begins. DOI explains the mechanism of adoption and can predict
if a new invention will succeed through the attributes of that innovation (Mohammed et
al., 2017a). Most studies have not used the HOT t model for assessing the human factors
in the adoption of cloud computing. Only one study incorporated HOT t to study the
acceptance of cloud in public services. The HOT model highlights the impact of human and
organizational elements (Yusof et al., 2008). Accordingly, aligning organization, technology,
and humans are signicant, as it is a starting point in IT implementation and investment.
Furthermore, the study argues that organizations need to prepare their sta to adopt
innovations or any organizational changes (Setiorini et al., 2021). HOT is flexible
and ts various elds, stakeholders’ perspectives and evaluation systems’ life cycles
(Yadegaridehkordi et al., 2020). Other researchers have found minimal utilization of HOT
(Sallehudin et al., 2019; Sharma et al., 2020). Nevertheless, some studies have merged
HOT with other models to study adoption (Alharbi et al., 2016; Lynn et al., 2020). This
research found a few studies (6 studies) that have concentrated on individual elements
for the adoption of cloud computing. It shows the need to look at the human element in
adoption studies. Human employees, for instance, play a great role in internal issues or
opportunities related to information technology.
DISCUSSION
The initial keyword searches exhibited that several papers are related to cloud computing.
Organizations have adopted cloud computing since 2009; however, it has not yet reached
maturity. Most of the papers have highlighted the factors for consideration while bringing
the benets of the technology to governments. The extracted papers have employed
dierent models to extract elements that decision-makers can consider in governments
before adopting cloud services.
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The studies also highlight how issues like privacy, security, data, infrastructure, cost,
and performance can be solved by using cloud computing. It depends on the government’s
choice to adopt cloud computing. Infrastructure issues can be solved as cloud computing
oers reduced costs on the infrastructure acquired and used with remote accessibility. For
instance, a study mentions that cloud computing SaaS can improve IT infrastructure costs
with fewer management concerns (Hadi & Omar, 2021).
Cloud computing has been highlighted to provide almost readily available hardware
that requires no prior capital (Avram, 2014). Besides, several promising upcoming start-ups
like Jungle Disk, Gigavox, SmugMug became possible with investments in information
technology with a lesser order of magnitude. As such, a cloud service is an adaptive
infrastructure that is possible to be shared by various clients, utilizing it in dierent ways.
The exibility of the infrastructure permits the balancing of computing loads even with
many users joining the system. It is an expansion in economies of scale.
RQ1: What is the research area in focus in cloud computing e-government?
It is signicant to note that this systematic literature review specically focuses
on adopting cloud services in e-governments but not in other elds like healthcare,
manufacturing, or retail. Hence, during the procedure of extracting the primary studies,
other elds of research emerged in the literature. The elds also discussed cloud computing
in their way; however, the extraction process was mainly on empirical articles that
concentrated on e-governments or the public sector. The benets of cloud services are
mentioned when looking at the growth of publications in the public sector or e-governments.
It could be because it needs lower infrastructure costs while performing well in ultra-large-
scale computing, exibility, scalability, on-demand services, and virtualization (Li et al.,
2021). Therefore, it has become an ecient solution to e-government development issues
like rising IT costs. According to the studies extracted, the focus areas were as follows:
Organizational models that will help in adopting cloud services (Mohammed et al.,
2017b; Salam & Ali, 2020; Shaque et al., 2017). They specify the determinants to be
considered for cloud adoption. Adoption of organizational innovation is key as it improves
the productivity of an organization, further enhancing economic growth while lowering
inequality (Ali et al., 2018b; Damanpour et al., 2018; park & Choi, 2019). These studies
focused on the organizational factors that are signicant for adopting cloud services in
e-governments. According to a study, the organizational adoption procedure is complex and
challenging (Wisdom et al., 2014). Adoption starts from an organization’s initial awareness
and examination of the innovation. Successful adoption is later seen when the innovation
is accepted and integrated into the rm, and individuals continue to use the technology for
some time (Hameed et al., 2012).
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Behavioral models examine the individual behavior towards the adoption of cloud
computing (Alkhwaldi et al., 2017; Lian, 2015; Sivathanu, 2018). It brings out the role
of humans in the adoption of e-government cloud services. Employees of an organization
play a role in internal issues or opportunities in an organization (Sharma et al., 2020). In
adopting innovations, the study points out that apart from the rm’s decision to pursue
adoption, the sta’s acceptance and initiation of their processes are also signicant (Wisdom
et al., 2014). It is because individuals have diculty deciding the right innovations for
solving specic issues or making adoption decisions. Besides, employee resistance to
information technology can be a barrier to innovation adoption (Sharma et al., 2020).
Therefore, individual characteristics can provide a comprehensive view of the adoption
of cloud services (Ali & Osmanaj, 2020). However, there are not many studies focusing
on the individual level of cloud adoption (AlKharusi & Al-Badi, 2016).
A framework for cloud adoption evaluating the procedure and factors for adoption was
discussed in a study (Junior et al., 2020; Shukur et al., 2018). From this study, it was seen
that very few studies adopted a framework. Frameworks allow organizations to follow
policies, standards, and guidelines (Chang et al., 2016). Moreover, they help organizations
overcome technical and organizational challenges. For instance, a study had extended the
technology acceptance model and TOE for cloud adoption (Gangwar et al., 2015). While
for secure cloud adoption, a framework was also developed to protect data (Chang &
Ramachandran, 2015)
This study also found some articles from developed countries (Ali et al., 2015; Polyviou
& Pouloudi, 2015), with the rest concentrating on developing countries. Accordingly, there
have been varying studies on cloud adoption in dierent parts of the world, with a higher
percentage (50%) for developing nations compared to lower than 155 for developed nations
(Vu et al., 2020). It may be one reason for the higher number of articles from developing
nations. Besides, adoption of cloud services is mentioned to be slow for public sectors,
with most being at the initial stages (Kuiper et al., 2014; Nanos et al., 2019). Therefore,
the slowness in developing nations is due to the lack of a favorable environment for the
utilization of cloud services (Vu et al., 2020). However, current governments are following
the adoption trend of cloud services (Mohammed et al., 2020).
RQ2: How is cloud computing used to improve service delivery in e-governments
(benets)?
Cloud computing with its models has a lot to oer for governments and the public
sector. Cloud computing is attractive because it eliminates the requirements for clients to
plan, allowing utilization of resources only when in demand. Cloud computing promises
to furnish every functionality of the existing information technology services model while
lowering the upfront costs of computing that make organizations shy away from utilizing
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cutting-edge IT services. Cloud pulls resources together like hardware, development
platforms, and/or services. It can be exploited via a pay-per-use model through customized
service level agreements. Cloud computing hence provides the ability of seamless access
to resources. Many governments struggle to manage citizen data, improve service delivery,
and enlarge their communication links through e-government. There are issues like data
duplication, fragmentation, traditional infrastructure, more costs on modernization, poor
performance, security, and privacy. A study agrees that cloud services can help enhance
the quality of services provided to citizens from e-government solutions, manage huge
data, and oer exibility and freedom (Ali et al., 2014; Mohammed & Ibrahim, 2015b).
As mentioned in this article, utilizing cloud computing can help handle the issues
mentioned above, but the bottom line is adopting the technology for use.
Based on the few issues reviewed, this study mentions how cloud computing can help
benet e-governments in various ways.
• Cost reduction- cloud computing is anticipated to reduce the cost of acquiring
physical hardware, hence saving nancial resources for organizations (Ali et
al., 2015; Lian, 2015; Liang et al., 2017; Shukur et al., 2018). Accordingly, cost
reduction is a promise achieved by adopting cloud services in organizations
with a positive inuence (Aziz et al., 2013; Kuiper et al., 2014; Mohammed &
Ibrahim, 2015a; Mohammed & Ibrahim, 2015b). Hence, cloud adoption can lower
maintenance and infrastructure costs while enhancing the availability of services.
It is possible by using an outsourcing model that permits the renting of resources
and paying only for the services used (Alkhater et al., 2014). Any upgrades and
maintenance are passed to the third party for responsibility and saving on costs.
• Lower IT infrastructure- this means that the cost of acquiring the hardware will
be low (Ali et al., 2015). This factor is linked to the rst factor on cost reduction.
Accordingly, lowering costs lowers infrastructure costs (Mohammed & Ibrahim,
2015a).
• Provide improved services- cloud computing will help lower risks and enable
accessibility of data anytime and anywhere (Ali et al., 2015; Lian, 2015; Shukur
et al., 2018). In turn, this will lead to better management of services and improved
eciency. When government services go online, it enhances the quality of services
in the areas of accessibility, time, and content (Dash & Pani, 2016). With cloud
computing, the increase of user loads only needs the addition and subtraction of
network load rather than the addition of hardware (Mohammed & Ibrahim, 2015a).
• Remote accessibility- cloud computing will permit access to rural and remote areas,
which increases audience reach (Ali et al., 2015; Liang et al., 2017; Shukur et al.,
2018). It also enables sharing of information. According to a study, since cloud
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services are web and internet-based, it brings accessibility via various internet-
enabled gadgets like tablets, laptops, and traditional computers, among others
(Mohammed & Ibrahim, 2015a; Tweneboah-Koduah et al., 2014).
• Backup and disaster recovery- cloud computing will enable functions to operate
even amidst unexpected eventualities (Ali et al., 2015; Liang et al., 2017). The
backup plan will help provide recovery when such incidents occur. Accordingly,
a study adds that backup and restores done on cloud services are easier than those
managed on physical storage (Dash & Pani, 2016; Mohammed & Ibrahim, 2015b).
Hence, the cloud process is simpler as compared to the traditional process.
RQ3: What factors, methods, levels of implementation, data analysis techniques, and
methodologies are available, and what is the gap for cloud computing in e-governments?
All the articles extracted in this study have highlighted signicant factors for cloud
adoption. It refers to the factors contributing to the successful adoption of cloud services
in governments. According to most studies, the elements related to the adoption of cloud
services fall into three main categories of technological, organizational, and environmental
levels (Ali et al., 2015; Ji & Liang, 2016; Liang et al., 2017; Polyviou & Pouloudi, 2015;
Shaque et al., 2017). However, some studies evaluated the factors based on behavioral
factors like performance expectancy, social inuence, facilitating conditions, perceived risk,
trust, and security (Alrashed & Alotaibi, 2017; Lian, 2015; Salam & Ali, 2020; Sivathanu,
2018). Other researchers considered dierent elements. For instance, Wahsh and Dhillon
(2015a) grouped the factors in terms of technical and non-technical elements, where the
technical entails elements like security, trust, compatibility, and complexity, and non-
technical elements include top management support, IT knowledge, relative advantage,
and technological readiness. Additionally, Wu et al. (2016) explained determinants in the
form of technological, business, and management factors. One study explores the adoption
of cloud from a framework (Junior et al., 2020). Shukur et al. (2018) explore the factors
from a framework and highlight the signicance of technological, organizational, and
environmental elements. Accordingly, other research has also pointed out the signicance
of environmental, organizational, and technological factors as key factors in the adoption of
cloud services (Kuiper et al., 2014). Other researchers have also agreed that organizational,
technical, and environmental factors have an impact on the adoption of cloud services (Al
Hadwer et al., 2021; Albugmi et al., 2016; Ji & Liang, 2016; Scholtz et al., 2016).
On the level of implementation, the articles extracted for this study fell into two
main levels: organizational and individual. Accordingly, 22 articles concentrated on the
organizational perspective of adoption, while only six articles considered adoption from
the individual perspective (Appendix A). There were no studies that merged both levels.
Adoption is a decision by a person to utilize innovation for the rst time, impacted by
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Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
attributes of the innovation, individual elements, and contextual factors (Sun & Jeyaraj,
2013). Accordingly, the adoption of innovations aects both the organizations as well as the
individuals (Hameed et al., 2012; Wisdom et al., 2014). Organizations are deemed complex,
while individuals have weights and may fail to choose the right innovation (Wisdom et
al., 2014). Dierent researchers have employed several data analysis techniques. These
include Partial Least Squares Structural Equation Modelling (PLS-SEM), factor analysis,
Statistical Packages for Social Sciences (SPSS), parsimonious model, MATLAB, Principal
component analysis with varimax rotation, ATLAS.ti, Manual & Leximancer visual text
tool, and logistic regression. However, PLS-SEM was the most employed analysis tool,
as shown in Appendix A. According to a study, PLS-SEM is mostly preferred as it attains
high extents of statistical power while exhibiting improved convergence behavior (Hair Jr
et al., 2014). In addition, it is good for complex models that may have many relationships
(Hwang et al., 2016). Moreover, because most studies were predicting models, PLS-SEM
suits the prediction of theories (Hair et al., 2013).
Methodologies have also been utilized in the extracted studies. This study found that
several researchers used the quantitative method with surveys for their data collection.
At the same time, the qualitative and mixed methods have not been largely used in cloud
adoption in e-government specically (Figure 4). Only three studies employed mixed
methods (Al Mudawi et al., 2019; Maluleka & Ruxwana, 2016; Oguntala et al., 2017).
Data gathering through surveys and analysis using the SEM method have been the most
employed methods. The quantitative method has been relevant in most studies in this
article, and a study mentions that this approach is more relevant when studying adoption
issues at the organizational level (Choudrie & Dwivedi, 2005). It could be a reason why
most studies were quantitative.
CONCLUSIONS
This study started with the motivation to understand cloud computing in e-governments
and how cloud computing can be adopted to support government services. It brought the
opportunity to rst perform a systematic review on cloud computing in e-governments and
know the progress in adoption. This study, in general, analyzed 654 studies from various
secondary materials. The articles were narrowed down to 94, and nally to 28 relevant
articles for this research. Our analysis reveals that very few empirical studies exist on the
adoption of cloud services. The organizational adoption of cloud computing started around
2011, but the researchers could only nd the rst empirical study from 2015. Therefore, the
study sought to explore signicant factors for cloud adoption to implement e-governments.
While most of our papers are specically on adoption factors with empirical support, the
results reveal that most of these studies were conducted in developing countries. The
study also reveals that most studies have concentrated on quantitative methods using
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surveys, with only a few using qualitative methods with case studies and semi-structured
interviews. This study also notes that the concentration on identifying factors has mostly
been done using quantitative procedures like structural equation modeling and regression
analysis. The ndings indicate that researchers have mostly resorted to employing the
TOE (13 studies) and DOI (12 studies) frameworks for studying the adoption factors.
Nevertheless, the researchers have also seen studies using UTAUT and TAM. Some studies
have equally combined the models for better understanding. Technological, environmental,
and organizational factors have been the most cited elements in research. Recent studies
have also emphasized the role of trust in cloud services, as this will inuence willingness
for adoption.
In developing countries, there is signicant growth in emerging technologies. The issues
mentioned include IT infrastructure, cost reductions, backup and recovery, availability,
and accessibility. For instance, cloud adoption for e-invoices in Taiwan mentions access,
availability of infrastructure, security, safety mechanisms, privacy, and data condentiality,
among issues hindering adoption. The utilization of cloud services in governments can help
handle such issues and bring improved service delivery. Considering the factors identied
in this study can help developing nations adopt cloud services.
SUGGESTIONS FOR FUTURE WORK
This study has examined how cloud computing can contribute to e-government issues.
The initial keyword searches for this study show that cloud computing has so many
possible solutions for healthcare, governments, manufacturing, and retail. This study,
however, concentrated on electronic governments. There are many applications for cloud
computing in e-governments; however, in a decentralized structure without trust, the
issues in e-governments may not be solved. Furthermore, cloud computing has evolved
with various service models (IaaS, PaaS, SaaS), and the adoption of a good service will
help handle infrastructure and cost issues in e-governments. From the outcomes of this
survey and the study observations, this article presents the following research directions
for cloud computing in e-governments that are worth considering for further evaluation.
Trust in Cloud computing: Trust has been mentioned as an issue in cloud computing,
and it is an area that needs much improvement. This study shows that very few studies
have considered the element of trust in the adoption of cloud computing in e-governments.
Little has been discussed about this factor concerning decisions to adopt cloud services
(Alrashed & Alotaibi, 2017). Trust can act as a moderator for the adoption of cloud
services. Governments are least trusted in storing condential and classied details on the
internet. There is diculty controlling sensitive information as a third party provides the
services. Trust is related to levels of condence (Sivapragash et al., 2019; Sivapragash et
al., 2012). While there has been a good amount of research evaluating determinants for
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Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
cloud computing, very few studies have evaluated the causal elements. Thus, there is a
need for future researchers to consider trust as the main factor, moderator, and/or mediator
to ll this gap in the literature.
Human and social factors for adoption: As mentioned earlier, and from this study, very
few researchers have considered the element of humans in the adoption of cloud computing
(Alkhwaldi et al., 2017; Lagzian et al., 2018). Furthermore, only one study mentions the
social factor as an element for cloud adoption (Alkhwaldi et al., 2017). Hence, there is a
need to explore the human and social elements for cloud adoption in governments.
Behavioral models for adoption: This study also discovered that only a few
researchers did empirical studies on behavioral models for the adoption of cloud services
in e-governments (Alrashed & Alotaibi, 2017; Sivathanu, 2018). Hence, research needs
to consider these models for government adoption studies.
This study found that most researchers have done quantitative studies. This methodology
is very predominant in adoption studies. However, there is a need to consider using mixed
methods for research studies related to cloud adoption in e-governments. Information
system researchers have promoted the utilization of mixed methods for stronger validity
and reliable outcomes (Ali & Osmanaj, 2020).
The SLR shows minimal studies in the domain of cloud computing in e-governments.
However, more studies rose in 2020 as compared to 2019. It means there is a need to further
grow the research in cloud computing in governments and public sectors.
This study also found frameworks with empirical results. However, very few studies
utilized this approach. Frameworks are good for a holistic view at both organizational and
individual levels. This study did not nd frameworks from an individual perspective with
empirical results. The frameworks adopted were from the organizational perspective. It
is another worth area consideration. Frameworks with empirical studies can strengthen
ndings and broaden the application of cloud computing in various contexts.
ACKNOWLEDGEMENT
The authors would like to express sincere appreciation to everyone who helped this study
along the way by providing advice and assistance.
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680
Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data
Analysis
Technique
Respondents
1Al Mudawi
et al.
(2019)
Factors
aecting cloud
adoption
Technological- compatibility,
complexity, service quality,
security, and relative advantage
2. Organizational- top
management support,
technological readiness,
organizational size
3. Environmental -competitive
pressure, regulations
4. Social attitude, trust,
awareness
Organizational TOE &
DOI
Mixed method SEM 400
2Ali and
Osmanaj
(2020)
e-government
services,
Infrastructure,
cost of
data and
applications,
IT budget
costs, software
licensing
and support,
integration,
and
management
1. Technological – Cost,
security concern
2. Organizational- top
management support,
organizational size, employees’
knowledge
3. Environment – Government
regulation, information
intensity
4.Innovationcharacteristics-
Compatibility, complexity
5. benets characteristics-
anticipated benets
Organizational TOE &
DOI &
DF
Quantitative Factor
analysis,
SEM
480 IT sta
APPENDIX A
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
681
Cloud Computing in E-Government
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data Analysis
Technique
Respondents
3Wahsh
and
Dhillon,
(2015a)
Factors aecting
adoption of cloud
for e-government
implementation
1. Technological – Security,
Trust, Compatibility,
Complexity
2. non-technological
factors – Top management
support, IT knowledge,
Technological readiness,
Relative advantage
Organizational TOE &
DOI
Quantitative SPSS with
AMOS
234 IT
experts
4Polyviou
and
Pouloudi
(2015)
Understanding
cloud adoption in
the public sector
1. Technological – Relative
advantage, compatibility,
complexity
2. Organizational –
interoperability, business
processes, environmental
standards, transparency of
process standards, security
standards
3. Environment –
Bureaucracy, political
matters, legal issues
Organizational TOE Qualitative Qualitative
software
21
interviews
across 6
European
countries
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
682
Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data
Analysis
Technique
Respondents
5Wu et al.
(2016)
Decision-
making
determinants
on public cloud
adoption in
e-government
1. Technical – alignment,
adaptation, security
2. Business – cost-
eectiveness, operational
risk
3. Management – IT
compliance, management
controlling power
Organizational Technical
adoption
theory
and IT
decision-
making
Quantitative SEM 227 CIOs
from public
sectors
6Salam and Ali
(2020)
Factors
inuencing
adoption
of cloud by
government
1. Performance
Expectations
2. Business expectations
3. Perception of
Availability
Organizational UTAUT Quantitative SEM 123
employees
7Mohammed
et al. (2017b)
Factors
inuencing
cloud adoption
in the public
sector
1. Fitness- Relative
advantage, compatibility,
trialability, security
2. Viability- return
on investment, asset
specicity
3. Technological
readiness- IT
infrastructure, IT policy,
and regulations
Organizational Fit
Viability &
DOI
Quantitative PLS SEM 296 IT sta
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
683
Cloud Computing in E-Government
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data
Analysis
Technique
Respondents
8Kandil et
al. (2018)
Eect of TOE on
cloud adoption in
Egypt
1. Technology – Relative
advantage, Complexity,
Compatibility, Security &
Trust
2. Organizational- Top
Management Support,
Technology readiness,
Maturity & Performance
Issues
3. Environment-
Competitive Pressure,
Telecommunication
Infrastructure, Internet
Service Provider, Trading
Partner support, Trading
Partner Pressure
Organizational TOE Quantitative PLS SEM 432 IT
employees
9Maluleka
and
Ruxwana
(2016)
Cloud computing
as an alternative
for the South
African public
sector
Lack of support, user
resistance, compatibility,
migration cost, lack of
approved standards, poor IT
infrastructure
Organizational DOI Mixed
methods
SPSS 28
questionnaires,
6 interviews
10 Al-
Rawahna
et al.
(2018)
Readiness of
government
organizations for
cloud computing
1. Top Management Support
2. Organizational Capability
3. Government Policy
4. Organizational Size
5. IT skills and
Infrastructure
Organizational TOE Quantitative PLS-SEM 132 IT sta
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
684
Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data Analysis
Technique
Respondents
11 Vu et al.
(2020)
Predictors of
cloud adoption
Legal System Quality,
Fixed Broadband
Penetration, Advanced
Digital Infrastructure,
Digital Legacy
Large Services
Organizational Institutional Quantitative Parsimonious
model
45 countries
12 Oguntala
et al. (2017)
Perception
toward cloud
adoption
On-demand service
deliver, guaranteed
quality of service,
scalability, and
exibility, data
security, user-centric
interface, user
autonomy
Organizational Literature Mixed
methods
Data
processing
software and
MATLAB
200
13 Liang et al.
(2019)
“Eects of
e-government
cloud
assimilation on
public value
creation”
Depth, breadth,
balanced t,
complementary t,
operational public
value, strategic public
value
Individual IT assimilation
theory, IT
value theory,
organizational
ambidexterity
theory
Quantitative PLS SEM 158 IT
directors and
senior IS
managers
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
685
Cloud Computing in E-Government
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data Analysis
Technique
Respondents
14 Sivathanu
(2018)
Elements
aecting adoption
of Digi Locker
cloud-based
e-governance
Performance
expectancy, eort
expectancy,
facilitating conditions,
social inuence,
perceived awareness,
computer self-ecacy,
multilingual option,
perceived quality of
information, perceived
response, perceived
trust
Individual e-GAM and
UTAUT
models
Quantitative PLS-SEM 80 citizens
and students
15 Junior et al.
(2020)
“Towards a
framework
for cloud
computing use by
governments”
Cloud characteristics Individual DOI and
Institutional
theory
Qualitative spreadsheets 17 Managers
and engineers
in charge of
Cloud Gov
16 Kyriakou et
al. (2020)
“Factors
aecting cloud
storage adoption
by Greek
municipalities
Relative advantage,
compatibility,
complexity
Organizational DOI Quantitative Principal
component
analysis
121
municipalities
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
686
Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data
Analysis
Technique
Respondents
17 Mousa
(2020)
Determinants
of cloud-based
e-government
Technological,
organizational, IT
knowledge
Organizational TOE & DOI Quantitative SEM 279 decision-
makers
18 Garad and
Santoso
(2017)
Impact of using
Cloud computing
in e-government
and infrastructure
required
Performance, security
and privacy, control,
data transfer costs,
accuracy and reliability
Organizational Framework Quantitative SPSS 136
managers
and IT
employees
19 Ji and Liang
(2016)
Exploring the
determinants
aecting
e-government
cloud adoption in
China
Technology,
organizational, and
environment
Organizational TOE & DOI Qualitative Qualitative
analysis
software
12 interviews
20 Shaque
et al. (2017)
Elements aecting
e-government and
cloud migration
Technological-
perceived benets,
IT infrastructure,
complexity,
Organizational- size,
top management
commitment and
innovativeness,
resource commitment
Environmental-
external pressure,
regulatory
environment, work
overload
Organizational TOE Quantitative Principal
component
factor
analysis
175
respondents
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
687
Cloud Computing in E-Government
No. Author Issues/
Themes
Factors Level Theory/
Model
Methodology Data
Analysis
Technique
Respondents
21 Liang
et al.
(2017)
Technology driving- comparative
advantage, technological concern
Cloud provider support- cloud
provider characteristic, cloud
provider competence, cloud
provider presence
Organizational readiness-
top management support,
organizational scale, and
complexity of informational
resource
Environmental stimulus- policy
& regulation, industry standards,
competition pressure, requirement
of citizen, best practice, nancial
fund
Cloud trust- initial trust, perceived
benet-based trust
Organizational Grounded
theory
Qualitative Atlas’s 24 government
ocials
22 Shukur
et al.
(2018)
Cloud
adoption
framework
for Iraqi
e-government
Technological- cost, scalability,
exibility, compatibility,
complexity, security & privacy,
resource utilization
Organizational- top management
support, IT infrastructure, IT
human resources
Environment- reliable, available,
ownership, mobile access,
migration
Ease of use,
Regulation issues
Organizational TOE &
TAM
Quantitative Mean &
SD
25
e-government
sta
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
688
Osama Abied, Othman Ibrahim and Siti Nuur-Ila Mat Kamal
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data
Analysis
Technique
Respondents
23 Lian (2015) Cloud-based
e-invoice
adoption
Eort expectation,
social inuence, trust in
e-government, perceived
risk
Individual UTAUT2 Quantitative PLS SEM 251 respondents
24 Alkhwaldi
et al. (2017)
Cloud-based
e-government
acceptance in
Jordan
Technological, Human,
Social, Finance
Individual UTAUTA2 Quantitative SPSS 164 respondents
25 Liang and
Qi (2017)
Determinants of
e-government
cloud adoption
in China
Environmental- nancial
commitment support,
completeness of policy
& standard, successful
cases
Organizational- top
management support,
organizational inertia,
scale, and complexity of
informational resources
Technology task t
Technology-
compatibility,
competitive advantage,
complexity
Organization DOI, TOE,
TAM, TTF
Qualitative:
multicast
Atlas’s 21 respondents
Pertanika J. Sci. & Technol. 30 (1): 655 - 689 (2022)
689
Cloud Computing in E-Government
No. Author Issues/Themes Factors Level Theory/
Model
Methodology Data Analysis
Technique
Respondents
26 Ali et al.
(2015)
Collaborative
cloud adoption
in Australian
municipal
government
Technological- Cost,
technology readiness, security
Organizational- Size, top
management support,
employee knowledge
Environment- Competitive
pressure, regulation support,
information intensity
Innovation factors- Relative
advantage, complexity,
compatibility
Organizational TOE &
DOI
Qualitative Manual &
Leximancer
visual text tool
21 interviews
27 Alrashed
and
Alotaibi
(2017)
Trust in
acceptance of
government
cloud
Performance expectancy, eort
expectancy, social inuence,
trust, perceived risk
Individual UTAUT Quantitative PLS-SEM 310 IT
professional
and
technicians
28 Lagzian
et al.
(2018)
Eective
factors for
acceptance of
cloud in Iran
public services
Human- recipients’ innovation,
decision makers’ knowledge
Technological- relative
advantage, test capability,
compatibility, technology
infrastructure, security, and
privacy
Organizational- information
intensity, employee knowledge
Environmental- External
support, environmental
infrastructure, competitive
pressure
Organizational TTF, Hot
t, DOI,
& TOE
Quantitative SPSS &
Logistic
regression
60 managers
and IT
experts
