Examining the Factors Influencing Adoption of Cloud Computing

Abstract

Governments are always trying to find ways to improve their services to citizens; and in order to achieve this they need to restructure their processes and use information technology (IT) effectively. This requires adequate infrastructure and appropriate regulations.Pressure to do this comes from citizens who increasingly have access to digital technologies and expect better e-services from their governments. Public sector organisations in Saudi Arabia, therefore, need to proactively implement technological innovation to enhance their services. One way to achieve this is to develop a cloud computing infrastructure and the appropriate applications. Cloud computing is understood, however, more needs to be known about how it impacts public service organisations and the provision of services.

This paper aims to identify and discuss the importance of particular factors pertaining to the fitness and viability of adopting the Cloud for Saudi public organisations. offers the most valuable insights for students seeking engineering dissertation help. The model that forms the theoretical framework for this integrates the Diffusion of Innovation (DOI) theory and the Fit-Viability Model (FVM) and the data was obtained from semi-structured interviews and questionnaires with 408 Saudi public sector employees working in the relevant IT departments.

The results indicate that relative advantage, compatibility and trialability are key variables influencing the fitness of cloud computing for Saudi government services. The findings also suggest that viability is influenced by return on investment (ROI), asset specificity, and support from top management and staff IT skills. The result of this investigation can help policy makers in public organizations in Saudi Arabia to determine the fitness and viability of cloud computing to improve their e-government implementation and enhance their service provision performance.

Keywords: Cloud Computing, Diffusion of Innovation Theory, E-government, Fit-Viability Theory

Introduction

E-government refers to the use of Information and Communication Technologies (ICT’s) to enhance the delivery of information and services to the citizenry, the business sector and the government sector [1]. Governments are thus able to make use of emerging technologies to offer these fully customised e-services. Cloud computing is one of the new technologies that can create and deliver cost-effective, user-centred public services; and it may revolutionize e-government implementation in the matter of actual and professional use of resources as well as cost-saving [2] [3] [4]. It has already revolutionised the way technology is used by individuals and organisations in other sectors, and established high efficiency in terms of scalability and availability [5] The key characteristics of cloud computing make it fit with e-government services requirements. Moreover, due to its advantages, many governments are applying cloud computing for providing e-services [6]. By using cloud services, organizations are seeking to control and disseminate their information, enhance IT infrastructure and reduce the cost.The Cloud is giving governments the opportunity to customize and improve their e-services [7].There are several examples of this, one such being the US federal government information portal (USA.gov) which adopted the Cloud to deal with long downtime, delays, massive network traffic loads, and the resulting inefficient services. As a result, their downtime went down 99.9%, site upgrade time reduced from 9 months to a single day with savings of 72% per annum. Many developing countries are facing issues in operating e-government services, such as the absence of basic IT infrastructures and knowledgeable staff and the lack of financial resources [8] [9] [10] [11].These countries are still at the early stage of developing e-government systems; and, as they have made a huge effort to launch these systems, they may benefit by considering the opportunities offered by cloud computing. Saudi Arabia is considered to be a technologically developing country [12] thuscloud computing adoption in Saudi Arabia is presumed slow compared to the developed countries [13]. One study conducted a survey to investigate the awareness of managers and employees regarding to the cloud computing; and the results showed that cloud computing is the new direction in Saudi’s organizations [14] However, it still has not received enough attention in Saudi Arabia and little research has been done to study the adoption of the Cloud more specifically in the context of public sector organizations. In order to rectify this, the current study seeks to answer the following research question: What are the factors that influence the fitness and viability of cloud computing for IT governance in Saudi public sector organisations?

Literature Review

There is little research that studies cloud computing in the context of public sector organizations. Mostly, previous researchers discuss the benefits and challenges of cloud computing for public sector organizations. Several studies have proposed models or frameworks to adopt cloud computing to implement e-services. However, the proposed models were mostly built on cloud service models (SaaS, PaaS, PaaS, Public, Private, and so on) or the available e-government models, thus layered models [15] [16] were developed. Researchers have been investigating cloud computing as an alternative technology to support public sector services since 2009. A review conducted on cloud computing in the public sector context showed that the reviewed studies mostly just proposed the benefits and challenges of implementing e-government using cloud computing based on technology characteristics and did not investigate them empirically [17].Cases from different countries were analysed with the intention of revealing the main drivers for adopting cloud computing in the public sector context; and cost saving and the scalability were identified as the main common drivers that stimulate organizations to adopt cloud computing [7]. Another review of cloud adoption driversconcluded that cost saving, efficient use of resources; high scalability of resources and less maintenance were significant [18]. However, relatively few researchers have examined the factors that affect cloud computing adoption in the context of public sector organizations [7] Another study of the factors affecting an organization’s decision to incorporate cloud computing as a part of its strategic IT plans proposed a conceptual model which identified cost saving, the need, reliability and the perceived security as significant and the results showed that these four factors positively affect the managements’ intention to use cloud computing [19] Also, [20]studied behavioural intention to adopt cloud computing for providing government services. The study model combined the Technology Acceptance Model(TAM) with specific constructs including availability, accessibility, security and privacy, and reliability. The proposed model was empirically verified by examining the perception of public agencies’ employees; and all perceived advantages of cloud services were perceived to have an effect on user intention and behaviour. The viability of cloud computing for implementing e-services in the U.S. Department of Defence (DoD) was investigated [21] Grounded on Fit-Viability Model (FVM), a Viability Willingness Model (VWM) was developed to examine the willingness of the DoD to use this technology. Results demonstrated that the cost, organizational inertia and the fitness of cloud computing lead to a viability perception, which leads to behavioural intentionto adopt cloud computing. A study which investigated the security, organizational need, reliability, and cost as the factors influencing the perceptions of IT leaders in developing countries to adopt cloud computing showed that IT leaders’ perception about these matters correlate positively with their willingness to adopt cloud computing [22]. Another developed a model for adopting cloud computing in governments and large enterprises; and found the influencing factors were identified by analysing a number of cases and the literature related to the Technology-Organisation-Environment TOE model, which assists organizations understanding the required capabilities for adopting cloud computing [23]. A case study of central public administration in Moldova was conducted to examine the ability of cloud computing to improve the value of public service provision [24]. The authors used a success model based on the DeLone&McLean (D&M) model and found that as well as actual use and intention to use, quality of system, information and service and user satisfaction were significant.Factors that may affect the decision to adopt cloud computing in Malaysian public agencies were explored and identified [25] The Diffusion of Innovation Theory (DOI) and characteristics of IT personnel were integrated to construct the research model. The findings indicated that relative advantage, compatibility and the IT personnel knowledge influence the Malaysian public sector’s decision to adopt cloud computing. Recently, in the context of Saudi Arabia, [26] examined factors affecting Saudi government organisations decision to adopt cloud computing, developeda model based on the literature, and conducted a survey in four Saudi government organisations to empirically verify the model. The results showed that the adoption of cloud computing technology was supported by 85.80% of the respondents; 97.63% of the respondents perceived cloud usefulness as the most critical, while 95.26% saw service quality and security as critical. Interestingly, respondents who perceived service quality as criticalhad a significantlyless favourable attitude to adoption. The factors affecting cloud storage adoption by public and private sectors in Saudi Arabia were analysed [27]. It was concluded that establishing cloud in any private or public sector raises numerous questionsabout cost, data connectivity quality, data safety and confidentiality; with the latter being of most concern.Mostly, employees in the private and public sector accepted that they would derive greater benefits from the use of cloud-based environment but that they needed regular training to handle cloud data safely. A value model comprising business, financial and technical aspects for cloud computing adoption in Saudi Arabia public organizations was proposed [28]. The study attempted to identify the business requirements for implementing cloud computing services in Saudi Arabia public organizations. The TOE theoretical framework and financial imperatives were used to analyse the business requirements. The study found that if business needs are to be properly supported by the organisations’ ICT, these costs need to be met. However, their model was not empirically tested. Similarly,[29] identified keytechnological, environmental, organizational and societalfactors to be considered by organizations when deciding to adopt cloud computing; and Saudi government agencies were proposed as a case study. However, no empirical study has yet been conducted to validate the proposed framework. Another study [30] investigated the factors influencing cloud adoption in Saudi Arabia. A framework was constructed based on primary and secondary research and verified by experts and presented to support decision makers about whether to adopt cloud computing. The theoretical foundations of the proposed framework were grounded on knowledge management, the literature of decision making, organizational learning and technology adoption and technology diffusion theories. The results show that the framework enhances the decision to adopt cloud computing. However, the factors were identified based on the preliminary field work, which was largely conducted with Cloud Service Providers (CSPs) and was limited to five enterprises, while the users from different types of enterprises and industry sectors were used to validate the proposed framework. This implies some differences in views between CSP experts and the cloud computing users which were reflected in the results. In addition, both government and private sector organisations were considered as the study population. Analysing these studies shows that there is no one model that has been consistently utilised to examine cloud computing adoption in the public sector. Due to a different theoretical backgrounds and different objectives and environments, previous studies investigated a wide range of factors influencing cloud computing adoption in the public sector. Further, a systematic review on cloud computing adoption factors concluded that cloud adoption research is in seminal stage and needs more studies [18].This indicates that there is a gap in the study of factors influencing cloud computing adoption in the context of IT governance in public sector organizations and the e-government context. Also, cloud computing has new characteristics compared to previous generations of computing, and the impacts of cloud computing innovation are not fully understood in the public organizations context and deserve more attention.

Theoretical Foundation and Proposed Model for Saudi E-Government Implementation

The adoption process of a new innovation is a sequence of steps that decision-making individuals have to pass thorough [31]. This process results in a decision (to accept or to reject) which can be made by individuals of a particular organization in a specific context [32].Within the context of this research, the factors influencing the decision of public organizations in Saudi Arabia to accept or reject cloud computing adoption are investigated. Based on the existing body of literature, there are few studies that have empirically examined the factors affecting the decision to adopt cloud computing in public organizations in Saudi Arabia. However, studies on e-commerce models can be considered to investigate factors affecting the acceptance of e-services in the public organizations [33] [34]. These usually comprehensive theoretical models encompass the Diffusion of Innovation (DOI) theory [31], the Technology Organization Environment (TOE) framework [35] and the Fit Viability Model (FVM) [36]. However, obviously one theoretical model alone cannot be applied to all kinds of innovations to be addressed; therefore, a mixed approach of theories is needed to identify the adoption process of an innovation [37]. Making a decision towards adopting a new technology might involve some risk; hence, developing a model that can help to estimate the fitness of a new technology within a given context will be worth proposing. In fact, the fitness of a new system or a technology may not only include the relevant technology features but also the viability of the application context. The Fit Viability Model (FVM) examines technological characteristics (fit) and organizational readiness (viability). FVM is considered to be an extension from Task-Technology Fit (TTF) which can provide a predication of system usage and performance [38] [39] [40]. Hence, FVM can be used as a foundation for a mixed model of cloud computing adoption for e-government implementation. The FVM is appropriate when examining technology adoptionespecially in organisations; and it has been applied into several studies conducted on mobile computing adoption [41] [36], decision in organizations in terms of social software fitness [42], business process management software including adoption of enterprise resource planning (ERP) [43] and government initiatives [44]. An evaluation of previous research depicts that, based on the context researchers outline distinct factors to evaluate the fitness dimension and measure fitness by determining some tasks of the context; subsequently, choosing a technology that has the characteristics that match with the requirements. The literature shows there is a positive indication for the relation of DOI factors (Relative advantage, compatibility, complexity and trialability and fit). Hence, this study uses DOI factors to measure the fitness of cloud computing technology within the Saudi public sectors to implement government services. H1: The fit of cloud computing to e-government task requirements positively affects Saudi public sectors` decisions to adopt the technology. H2: The viability of cloud computing positively affects the Saudi public sector`s intention to adopt the technology. Fit: Fit is proposed by [39] as the extent to which the technology capabilities can match the task requirements of an organization. Similarly, fit is described as the extent to which a technology can offer functionalities that can fit the requirements of the task [45]. Fit can thus be measured by the extent of which a feature of a technology can meet and satisfy the need of the requirement [36]. In this study, fit is measured by the extent to which cloud computing is reliable for the requirements of e-government operations. Task: Task features refer to the task requirements within the firm [36]; and can be behaviour requirements or ability requirements [46]. In this study, the task construct measures the requirement of the government and the actions that are conducted to deliver e-government services, i.e. it assesses the computing needs of government organizations to operate e-services. Launching e-government services online requires upgrading and operating the government systems to meet the task requirements [47] [48]. Therefore, in this study the following hypotheses are proposed: H1a: The E-government-related task requirements positively affect the fitness of cloud computing for implementing e-government services. Technology characteristics: by analyzing the technological factors affecting the adoption of cloud computing in previous studies in the literature [49][50] [51][52] [53], relative advantage, compatibility, complexity, trialability and security are proposed as the factors to assess the technology features of cloud computing fitness for implementing e-government services. Also, reviewing the literature indicates that there is a correlation between the fit construct and these factors. This research therefore proposes the following hypothesis: H1b: Relative advantage positively affects the cloud computing fitness to public organizations` computing needs for e-government services implementation. H1c: Compatibility positively impacts the cloud computing fitness to public organizations` computing needs for e-government services implementation. H1d: Complexity negatively impacts the cloud computing fitness to public organizations` computing needs for e-government services implementation. H1e: Trialability positively impacts the cloud computing fitness to public organizations` computing needs for e-government services implementation. H1f: Security negatively affects the cloud computing fitness to public organizations` computing needs for e-government services implementation. Viability: There are a number of factors affecting the organization’s viability when adopting a new technology. Viability has been defined and proposed in the literature in various ways; for example, [41] examined viability by assessing economic feasibility, IT infrastructure and top management support. To be ready to operate e-government services, cloud computing, as a new paradigm with open standards, will need knowledgeable individuals and provision from top management to assess its economic feasibility and analyze the technological readiness of the organization. As a result, this study measures the viability of cloud computing in the public sector by examining economic feasibility, organization and technological readiness. Economic feasibility: Refers to the degree to which the economic benefits to be achieved exceed the economic cost. Whether or not a specific technology/application is profitable can be determined through its economic feasibility. It also refers to whether or not a technology can reduce the cost and can provide a satisfactory return on investment (ROI). Therefore, it consists of two different parts: ROI and transaction costs. ROI examines the benefit vs. the cost of a specific IT project to demonstrate if the investment can provide acceptable return. However, users` willingness to adopt a technology is likely to increase if the transaction costs are low. Elements affecting the transaction costs can differ from one technology to another. For instance, in the context of mobile technology adoption, [37] discussed asset specificity, uncertainty and frequency whereas [42] identified employee training cost, compatibility cost and software/hardware maintenance costs. In terms of cloud computing adoption, uncertainty [49][54]and asset specificity [55][56] are found to be significantly affecting factors. Asset specificity: According to [37] this refers to specifying the assets that are needed for organizations when implementing a new system or adopting a new technology. The cost of obtaining hardware and software as well as the cost of integration of cloud computing adoption in hospitals were investigated [56]. In this study, asset specificity can be seen and defined as the cost of human (consulting and training) and physical (software, hardware, integrating and licensing) requirements to successfully adopt cloud computing to implement e-government services. Asset specificity can have a positive effect on the viability of cloud computing adoption as cloud computing can reduce the cost of obtaining heavy infrastructures. However, uncertainty means the extent to which an adopter has inadequate awareness about describing the outcomes of using a new technology [57]. Uncertainty was also defined as an element that economically influences mobile technology for an organization [36]. In term of cloud computing, concerns about data storage and access control increase the level uncertainty. In the literature, uncertainty has been examined as a negative factor to the adoption of a technology; and investigated as a negative influencer to the adoption of cloud computing [49]. Moreover, uncertainty can increase transaction costs due to the high risk [58]Subsequently, the transaction costs can be impacted by cloud computing uncertainty of public sectors which in turn can economically affect the viability of cloud computing in government implementation context. Hence, this study proposes the following hypotheses: H2a: The viability of cloud computing to e-government implementation is positivity affected by return on investment (ROI). H2b: The viability of cloud computing to e-government implementation is positivity affected by asset specificity. H2c: The viability of cloud computing to e-government implementation is negatively affected by uncertainty. Based on the literature, the viability of an organization to run a new technology or a new system can certainly be affected by a number of organizational factors. Project team knowledge of IT [59] [60] and top management support [60][61 are influencers of this type. Factors influencing the readiness of an organization have been presented in different ways:[36] investigated top management support and user competences to assess the viability of mobile technology in business organizations; and[42] studied employee training and top management support to measure the viability of an organization to implement social networking. In relation to cloud computing, academics have examined the influence of factors (top management support, cloud awareness, and prior background on the adoption of cloud computing) in the private sectors [62] [52]. Thus, top management support and cloud knowledge are key factors to be assessed on the cloud computing viability for government implementation. The following hypotheses are therefore proposed. H2d: Top management support positively affects the viability of cloud computing for implementing e-government. H2e: Cloud awareness positively affects the viability of cloud computing for e-government implementation. Technological Readiness: Refers to the organizational resources that impact the organization’s intention to adopt a new system or a technology. Organizational resources encompass IT staff and IT infrastructure [63][64][65] [66]. Due to the lack of standards for utilizing cloud computing, open standards for the cloud should be recommended by governments [67]. The influence of technology readiness on the decision of cloud computing adoption have been examined by different researchers; for example,[62] measured readiness based on IT human resources and IT infrastructure. Also, [52] [51] [68][69][54][70][71]explored the influence of organizational readiness in respect to knowledge of human resources on cloud computing adoption decision and issues of privacy. In terms of this study, IT infrastructure, skills and policies are chosen to examine the effect of technological readiness on the viability of cloud computing. IT infrastructure means the computing resources that are available in an organization [72]. The capability of the existing ICT infrastructure within the organization, and whether it can run and integrate the new system, has an important impact on the decision to adopt or not adopt the new system. Adopting a new technology or system requires experienced individuals with the organization, as the capability and skills of IT employees increase the potential of successful execution of the new system. Furthermore, the adoption of a new system can be influenced by governmental policies and IT regulation [73]. IT policy refers organizational and government requirements including guidelines, standards, regulations, laws or directives which resolve IT issues such as security and privacy, availability, and accessibility. This study proposes the following hypotheses: H2f: The perceived viability of cloud computing for offering e-government services is positively affected by IT Infrastructure. H2g: The perceived viability of cloud computing for offering e-government services is positivelyaffected byIT Skills. H2h: The perceived viability of cloud computing for offering e-government services is positively affected by IT Policies. Corresponding hypotheses along with the proposed model are shown in Figure 1.

IV Research Methodology

The research model (see Figure 1) was verified by conducting a study comprising semi-structured interviews with managers in charge of e-government projects in Saudi public sector organisations and a questionnaire survey with employees in those projects. The research model and hypotheses were tested with the SMARTPLS tool. Questionnaire Design The questionnaire design was based on the Diffusion of Innovation Theory and Fit Viability Model, as well as the literature of cloud computing adoption. The questionnaire contains two sections to assess the respondent’s perceptions of the two dimensions shown in the proposed model, Fit and Viability. The first section of the questionnaire uses the DOI construct scale to assess how cloud computing technology matches the tasks of implementing e-government services. The second section asks respondents to give their views on the extent to which their organisation is ready for cloud computing and contains three measures: economic feasibility, organizational factors and technological readiness. All items are based ona Likert scale of 5, where 1 = strongly disagree and 5 = strongly agree. In the context of this study, e various tests were applied to examine the reliability and vitality of the questionnaire, such as validity of content, pilot study and pre-testing. In order to examine the validity of content, a number of senior researchers examined the items in each section to verify that they accurately and comprehensivelydescribed the complete range of items. The questionnaire was modified in line with the feedback provided.A pre-test was conducted whereby experts in the field provided feedback on the clarity and wording of the questionnaire to enhance its validity. Finally, a pilot study was carried out with a small number of IT specialists to check the appropriateness of the questionnaire items and to eliminate any redundancy or misunderstanding. Top IT managers within the public sectors in Saudi Arabia were contacted and visited in person to explain the objectives of the research and the survey. These were from a wide range of organizations with different levels of experience and characteristics of e-government implementation. The managers then distributed copies of the questionnaire to their staff. A total of 500 samples were given and 408 were returned. SEM-PLS follows two-stage analytical procedure, measurement model assessment, and structural model assessment[74]. In the measurement model assessment stage, we examined the reliability and validity of the constructs while in structural model assessment stage, the proposed hypotheses were verified.

Firstly, the respondents were asked to provide their level of education, field of study, their occupational role and their length of experience. This was in order to acquire a profile of the respondents’ qualifications and area of expertise. All respondents had higher education level qualifications ranging from Diplomas (20.58%) to Bachelors (69.36%) Masters (6.86%) or PhDs (3.16%) Around two thirds were qualified in either Computer Science (30.14%) or IT (33.57%) while the rest had qualifications in English (20.34%) or Management (5.39%). In terms of their occupational roles, 180 respondents (44.11%) were ITManagers, 60 were in network architects (14.7%), 53 were engineers (12.99%) and there were the same number of technicians; 26 were programmers (5.39%); 8 were consultants (1.96%)and there were 4 database administrators (0.98%). 162 respondents had over 10 years experience (39.7%), 108 had 1-5 years’ experience (26.47%), 83 had 6-10 years’ experience (20.34%) and 55 had less than 1 year (13.48%). In order to verify the research model, Structural Equation Modelling using Partial Least Squares (SEM-PLS) was applied to analyze the collected data. In this research, to in order to examine the reliability of the construct’s measurements, three indicators were used internal consistency (item loadings), Composite Reliability (CR), and Cronbach’s Alpha (CA)[56][43]. As shown in Table 1, all item loadings exceed the minimum cut off point of 0.50 [75] indicating satisfactory internal consistency. In terms of composite reliability, all values are above 0.7, which is the satisfactory level suggested by [75] [76] and [77]. For Cronbach’s Alpha, all items also are above the minimum criteria of satisfactory (0.7)[78]. Therefore, the results showed sufficient evidence of the model measurement reliability. However, the validity of the model measurement was examined by using convergent and discriminant validity. For convergent validity, the Average Variance Extracted (AVE) was used and the results depict that the values meet the minimum criteria of 0.50 [78] [79], which means that the items in each construct share more than 50% of its variance. For discriminant validity (see Table 2), the square root of AVE for each itemhas a greater value than the inter-correlations of the construct with other items[79], which indicates that each construct is distinct and captures phenomena not represented by other constructs.

Table 1: Reliability and Validity Measures

Structural model

For verifying the model hypotheses, we estimated the significance of each path using a PLS bootstrapping method [77] utilizing 408samples. As shown in Table 2, the value of the path coefficients indicates the strengths of relationships between the variables. Furthermore, the value of the R2 depicts the amount of variance explained by independent variables. The R2 values for the dependent variables Fit, Viability and Adoption are 0.269, 0.7 and 0.288 respectively. These values show that the innovation factors with task characteristics explain about 27% of the fitness of cloud computing to implement e-government services, while about 70% of the viability is explained by factors such as ROI, uncertainty, TMS, IT infrastructure and IT skills. Also, 29% of the decision to adopt cloud computing is contributed by fit and viability. Table 2 presents the results of testingthe hypotheses. Hypotheses H1c, H1d, H1f, H2c, H2e and H2h are rejected while the rest are accepted.

Table 2: Hypotheses Testing Results

V Discussion of Results

Based on the findings, cloud computing fitness and its viability for e-government services implementation have significant relationships with the adoption decision. As shown in Figure 1, the path coefficient and t test related to fit and adoption constructs relationship in the model are 0.505 and 15.419 respectively, which indicates a strong relationship, while the corresponding values for the relationship between the viability and adoption are 0.065 and 2.17 respectively, which indicates weak (but significant) relationship. In addition, the results depict that cloud computing is fit for Saudi e-government services implementation requirements. The related hypothesis is supported by a path coefficient (0.257) and t test (7.931), which shows that specifying the requirements to be performed using cloud computing has a significant role as a predictor of the fitness for implementing cloud computing in Saudi e-government. Furthermore, innovation factors including relative advantage and trialability influences the fitness of cloud computing for e-government implementation with significant path coefficients and t test values (see Table 6). However, the resultsdepict that the relationships between variables such as security, compatibility, and complexity, and the fitness of cloud computing to the e-government implementation tasks are not significant. It seems surprising that security was not perceived as significantas cloud data is available to the provider. However, a possible explanation is that in 2020, Saudi Arabia obtained its own cloud computing service, Deem, which services both the private and public sectors (including the government). They state that their core values ‘start and end with security [80]. The Saudi Data and Artificial Intelligence Authority revealed the official identity of the governmental cloud DEEM and stressed that it enabled government organisations to focus on developing their services, ensuring data security and efficient spending on digital infrastructure [81].Given the establishment of this new local service, participants may have not considered security as a barrier to cloud adoption. Furthermore, the viability of cloud computing for e-government services implementation is affected by factors such as ROI assets specificity, top management support and IT skills. The related hypotheses (H2a, H2b, H2d, and H2g) are supported bysignificant path coefficient and t test results (see Table 6). On the other hand, the results show no significant relationships between uncertainty, cloud knowledge, IT infrastructure and IT policy, and the cloud viability for e-government services implementation. These results are perhaps a reflection of the advances that Saudi government has made in digitalising its services.

Conclusion

Saudi Public organizations are considered to be at the early stage of adopting cloud computing which has made them look for ways to improve their performance and operation. On other hand, for a sector to adopt cloud computing, a number of organizational and technological factors need to be examined. Hence, this study examines the fitness of cloud computing to e-government services through measuring its fitness for the related tasks in the Saudi public sector. Similarly, the viability of an organization needs investigation if a new innovation is being considered. The FVM was chosen to measure the factors influencing the fitness and viability of cloud computing adoption to the Saudi Government. Due to the fact that most of previous studies relied on only one methodwhen examining the factors affecting cloud computing adoption, an integrated method of FVM and DOI is used in this research to gain a deeper understanding. Regarding the implication for practice, the results show that complexity and security do not support the decision to adopt cloud computing. However, economic factors (ROI and asset specificity) and organizational factors (top management support and IT skills) do influence the viability of cloud computing adoption for Saudi government implementation. Further, the degree of fit has a higher impact on the decision than viability to implement cloud computing in Saudi Arabia. To conclude, this research model offers decision-makers a way of evaluating whether or not cloud computing is a good fit for the services they are offering and the degree to which their organization is viable to adopt this technology.

While this research contributes to an understanding of cloud adoption in a developing context such as Saudi Arabia, it is still limited in some areas. Firstly, the size of the sample taken in this study was relatively small. Secondly, time constraints meant that it was not possible to conduct interviews to gather qualitative data that could shed light on the reasons that lie behind the study’s results. It is very early days for the Saudi cloud, therefore, further investigation is recommended.

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