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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
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