Received 31 March 2016; accepted 28 May 2016; published 31 May 2016
Global competition places huge pressure on organizations to reduce cost, increase profitability and enhance productivity, in order to survive in this rapidly changing environment  -  . This has encouraged information technology (IT) managers to adopt the most up-to-date technologies that enable them to reduce costs, sustain competitive advantage and improve the bottom line  -  . The use of information Technology can improve the effectiveness of businesses and provide a positive advantage to organizations   . As information technology services are becoming increasingly expensive and time consuming, adoption of cloud computing has evolved as a major technological innovation to reduce these processing costs through enhancing reliability, flexibility, availability and processing throughput  -  . Recently, cloud computing has been an important concept in the field of Information Technology; it is recognized as an important area of Information Technology investment  -  . Cloud computing is considered a new phenomenon that provides opportunities for organizations, by offering a large collections of easily accessible virtual computer resources  , and it has the possibility for facilitating economic growth by offering existing implemented remote infrastructure for computing and data management needs with lower initial investment capital. Nevertheless, the challenge remains to determine the factors that lead organizations to adopt and deploy cloud computing  . Cloud computing technologies have become a serious target in the field of information system development; it provides organizations with different advantages such as resource pooling, rapid elasticity, broad network access…etc.  .
Cloud computing is considered a new Information Technology innovation phenomenon. It has been developed from the idea of sharing and standardizing the resources in a centralized environment  . Adopting new technologies like cloud computing will help many organizations to gain a competitive advantage and allows them to become more efficient and productive  . Cloud computing is changing the way organizations buy, sell and deal with customer; moreover, it is also becoming an essential part of the organization’s strategies  .
The adoption of the newest technologies, like cloud computing, plays an essential role in the ability of organizations to maintain a competitive position in the marketplace, and has become a core strategy to ensure effective management of IT resources   . Nevertheless, the decision whether to adopt a cloud computing model is often complicated by challenges and uncertainties about the expected business value related to the new technology  . Different studies have discussed the Technological, Organizational and Environmental factors (TOE) that have impact on the cloud computing adoption. However, there is still a need to analyze the adoption of this technology in different business sectors to have a better understanding of cloud computing  .
Jordan is considered as a desirable location for investment in the Healthcare sector. Jordan hospitals are investing heavily in modern technology to sustain its reputation of providing high quality and affordable healthcare. Patients from around the world fly to Jordan for medical treatment, with over 250,000 patients travelled to Jordan in 2012 and the number is increasing each year  . Even though the sector has been growing in recent years, it still suffers from various challenges; such as pressure to decrease costs, intense competition, the difficulties of managing information as people and organizations integrate, continuing to gain and sustain a competitive advantage through growth and diversification, the convergence in considering suppliers, payer sources, providers and customers. With these emerging challenges comes the need to access information and services from anywhere  . Cloud computing is significantly changing the implementation and adoption of health care information technology, specifically for the development of electronic health record   . Cloud based healthcare information is rapidly becoming a leading trend for the healthcare information system development worldwide  , as the new IT platform has positively changed the structure and nature of the hospital's information system  . However, according to reference  hospitals must be carefully evaluated when deciding to adopt this new IT innovation.
According to  , there are many researches that studied cloud computing architecture  , potential application  and benefits and Costs  . Unfortunately, few experimental studies that studied the adoption of cloud computing in the Arab world in general and Jordan in particular are available. Because of the lack of such studies, this study provides clear understanding to the influence of TOE factors on the adoption of cloud computing. This research is carried out to understand how TOE factors affect cloud computing adoption in Jordanian Hospitals. The findings of this research can help organizations, more specifically hospitals in Jordan to, firstly, better understand cloud computing itself and, secondly, how Cloud computing can increase hospitals’ effectiveness. Moreover, this study can be considered as guidelines to how TOE factors can affect the decision of whether to invest in adoption cloud computing model or not.
2. Literature Review
2.1. Cloud Computing
The future of Information systems will depend on cloud computing technology; this is because it can reduce the costs of IT services at the same of increasing the reliability and flexibility  . Moreover, it is regarded as a potential solution to improving organizations’ IT competitiveness and performance   -  .
Cloud computing has three service models; first, infrastructure as a system (IaaS). It is known as the fundamental level of cloud services, which delivers infrastructure services to customers over a network like hardware and software  . Platform as a service (PaaS) is the second level of cloud computing. It offers online access to every resource that is needed to build an application. The services include; application design, development, testing, deployment and hosting tools, which provide access to programming languages and libraries  . The third service model is Software as a service (SaaS). It is known for providing users with a piece of software over a network such as internet, where it enables users to install the software and use the application anytime and anywhere they have access to the network  . It also provides an agile updating for applications as the service provider hosting the application systems performs updates that take place seemingly without any scheduled downtime, and it helps with the removal of legacy systems which helps organizations to extend their software application into other global regions   .
There are many problems with the adoption of cloud computing. One of them is that are no clear understanding of the relationship between TOE factors and the adoption of cloud computing  . The adoption of cloud computing will be perceived positively by organizations if they have an adequate budget, human resource support, ample time, good top management involvement and other factors  .
2.2. TOE Framework
TOE framework was developed by Reference  mainly to study the adoption of Information Systems inside business organizations. This framework is becoming an important theoretical guideline for Information Technology adoption  . According to reference  , the adoption of complex IT innovation requires an advantageous technology portfolio, organizational structure, and environmental strategy. For the purpose of this study, the theoretical model is needed in order to get better understanding for this technology.
The current study stipulated that three components are relied upon to determine the intention of organizations to embrace cloud computing, these are: Technological, Organizational and Environmental. The incorporation of TOE elements has leaded it to become more valuable compared to other models in studying technology adoption  .
2.2.1. Technological Context
Technological context means the internal and external technologies that organizations can use in their business  . Internal technologies are those that are already in use at the firm, while external are those available in the market place and not using by the organization  . Technologies that are currently in use by the firm influence decision of adopting cloud computing because they determine the scope and limit of the technological change that the firm can accept. Technologies not in use by the firm and exist in the marketplace influence adoption decision by indicating how firms can evolve by accepting new technologies. The changes brought about by technologies that exist beyond an organization’s boundaries include incremental, synthetic, or discontinuous changes. Technologies that offer incremental changes only add new features to existing technologies and are regarded as the least risky of the three. Synthetic changes result when existing technologies are combined in novel ways. These kinds of changes are considered moderately risky. Discontinuous changes are technologies that are radically different from existing ones  . Although the successful adoption of IT depends to a large degree on the technology competence of the organization  , there is a dearth of studies that take technological characteristics into account when studying factors affecting IT adoption decision  . Technological Context can be discussed from three point of views; Relative Advantage, Complexity and Compatibility.
1) Relative Advantage
Relative Advantage is defined as the level to which a Technological factor has more benefits that disadvantages to the organizations  . It is logical for organizations to weigh the benefits that are expected to come from adopting an innovation  . It has been reported that the probability of adopting a new technology increases when firms perceive a relative advantage in that innovation  . Cloud computing promises various advantages to organizations that adopt it such as speed of business communication, efficient coordination among firms, better customer communication, and access to market information mobilization  . Other benefits of cloud computing includes reduced costs, scalability, flexibility, mobility, pay-per-use, and shared resources   . Organizations can avoid expenses associated with owning and maintaining an IT infrastructure that is not fully utilized by using cloud computing, thereby radically reducing the total cost of IT operations  . Cloud computing also offers rented service where organizations pay-per-use which leads to adjusting the level of usage according to the organization’s current needs  . Furthermore, as the requirements for cloud computing increase, the user is able to scale up resources and infrastructure to satisfy new requirements  . In terms of flexibility, cloud computing allows users to access and works with documents from any place and any time given that they have access to a computer and an internet connection. Moreover, the ability to offer shared resources is another advantage of cloud computing that enables employees to access resources placed on cloud regardless of their location, thus saving businesses a lot of time and money  .
Complexity can be defined as the perceived degree of difficulty of understanding and using a technology  . It is related to time taken to perform tasks, integration with cloud infrastructure, efficiency of data transfer, system functionality, and interface design  . According to reference  , the probability of adopting a new innovation will be less likely if it is seen as more challenging to use. Adopting new technologies may present organizations with challenges such as changing the processes that interact with their business systems  . In order to increase the chances for adoption success, technologies should be user friendly, manageable, and easy to use   . Furthermore, cloud computing is still in its early stages which may scare organizations away from adopting such a new technology  .
Compatibility refers to “the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters”  . Perceived compatibility takes into consideration whether current values, behavioral patterns, and experiences of an organization and its members are consistent with a new technology  . Increased compatibility between an innovation and adopters’ needs facilitate an easy integration of the technology within the organization and business functions. Compatibility can provide adopters with several benefits. For instance, it can result in time and cost reductions as users will not have to deconstruct a costly infrastructure if a new technology was adopted  . The incompatibility between the features of the innovation and the potential adopters’ needs and business processes is considered a major barrier affecting the adoption of that innovation  . The more the technology is recognized as being compatible with existing systems and organizational values and beliefs, the more likely organizations are to think about adopting cloud computing. Cloud computing allows organizations to keep up with new technology without affecting existing legacy systems aligned with their different organizational, managerial, and operational needs  .
2.2.2. Organizational Context
Organizational context can be defined as the resources and characteristics of the firm  . In this study the organizational context is composed of two main components. The first part is top management support while the second part is technological readiness.
1) Top Management Support
Top management support plays a significant role in initiating, implementing, and adopting of information technology  . Their support can be seen in their sponsoring of initiatives and engaging in the adoption of new technologies within the organization. Top managers are responsible for setting organizational strategy and for establishing direction for technologies such as cloud computing. Top managers can secure enough resources and produce a supportive climate for cloud computing  . Top management awareness of potential benefits of adopting cloud computing is regarded as essential to manage potential organizational change through an expressed vision and commitment, sending positive signals of confidence in the new technology to all employees of the firm  . Taking in such support helps the organization to avoid any internal barriers and opposition to change. It can be concluded that top management support is vital for organizations searching to produce a competitive environment, whilst also providing the resources needed to adopt cloud service  .
2) Technological Readiness
The technological readiness means the readiness of infrastructure and IT human resources which influence the adoption of a new technology   . Reference  referred to technological infrastructure as “installed network technologies, and enterprise systems, which provide a platform on which the cloud computing application can be built”. IT human resources are considered the sources of knowledge and skills that are needed to implement cloud computing related IT applications  . Organizations can be segmented into five different groups based on their technology readiness, from explorers who are the first to adopt a new technology, to laggards who are the last to adopt a new technology and are not technologically motivated.
2.2.3. Environmental Context
Environmental Context covers the small environment where the organization runs their business including industry market as well as Technology Service Providers  . Environmental context refers to a firm’s industry, competitors, and government policy or intention   . The environmental factors used in the study include competitive pressure, trading partner pressure, and vendor scarcity.
1) Competitive Pressure
According to  , Competitive pressure is the degree of pressure which organizations can face from their rivals in the same industry. This Competition can play a positive role in the adoption of any new technology especially when the technology affects the competition  . Adopting technology helps organizations in changing the competitive environment in different ways such as industry structure and outperforming competitors. Cloud computing can increase the operating efficiency, data accuracy, and decrease costs  . Therefore, organizations that are first to adopt cloud computing are expected to derive benefits in terms of competitive advantage and survival  .
2) Trading Partner Pressure
In cloud computing, trading partners relate to the cloud service providers. Organizations, regardless of size, rely on the experience and skills of trading partners when looking to adopt cloud services. Trading partner previous history and past projects can affect on the decision of whether to adopt a new Information Technology innovation or not  . Organizations that want to adopt cloud services are concerned about the ability of service providers to ensure the availability of data when needed. To ensure the desired level of availability, service level agreements and a combination of precautionary measures can be used. Security is another concern organizations have with regards to trading partners. Cloud computing security is more than just authenticity, authorization, and accountability; it is also related to data protection, disaster recovery, and business continuity. Privacy and confidentiality also relate to security because service providers have access to all the data and could intentionally or unintentionally use it for unauthorized purposes. Consequently, many companies are reluctant to host their data on external computers that might be co-hosted with other companies’ application  .
3) Vendor Scarcity
Vendor scarcity refers to the lack of reputable and qualified cloud service vendors in the cloud service market. Given that cloud service is still a fairly new market, existing knowledge or experience about the cloud service may be limited. Having a limited number of vendors may in turn result in lower service quality. Thus, the availability of enough vendors with good reputation improves the organization’s confidence in cloud services and lets them make a positive trusting attitude towards cloud services transformation. As such, vendor scarcity will have a negative influence on firm’s trust towards cloud service  .
2.3. Factors Affecting Cloud Computing Adoption
Many studies have been undertaken in an effort to understand different factors that are expected to influence the decision to adopt various technologies such as  . With regards to cloud computing, researchers have chosen different ways to explain what encourages or discourages organizations to adopt cloud computing. Reference  , for instance, examined the effect of eight factors: “relative advantage, complexity, compatibility, top management support, firm size, technology readiness, competitive pressure, and trading partner pressure” on the decision of high-tech companies to adopt cloud computing. The findings indicated that five of these factors, namely:“relative advantage, top management support, firm size, competitive pressure, and trading partner pressure, significantly affected the adoption of cloud computing”. Reference  “investigated the influence of the TOE framework on the adoption of cloud computing in SMEs”. The factors included in this study were technology factors (“relative advantage, uncertainty, compatibility, complexity, and trainability”), organizational factors (“size, top management support, innovativeness, and prior IT experience”), and environmental factors (“competitive pressure, industry, market scope, supplier efforts and external computing support”). The results showed that most of these elements had a significant effect on the adoption of cloud services in SMEs. The only factor that was not found to have any contribution in the process of adopting cloud computing was competitive pressure. In addition, reference  used the TOE framework to determine which factors influence the decision of managers to adopt cloud computing in the UK. The results indicated that the following four factors had positive impact on the adoption: “competitive pressure, complexity, technology readiness and trading partner pressure”.
Reference  studied the effect of various factors on the decision of hospitals in Taiwan to adopt cloud computing. The study revealed that the five most critical factors were data security, perceived technical competence, cost, top manager support, and complexity. Further, it was noted that among the four dimensions proposed to influence the adoption of cloud computing, the most important one was technology, followed by human, organizational, and environmental factors. Moreover, a study was conducted by reference  with the aim of identifying the factors with the most influence on the intention of organizations to adopt cloud services. The study found that the factors of availability, reliability, security, privacy and others had a significant impact on the decision to adopt cloud computing. Only trading partner pressure which not. Reference  also tried to understand which factors influenced the adoption of cloud computing in organizations. The researchers used an integrated model composed of both Technology Acceptance Model (TAM) and TOE factors in addition to two mediating variables including perceived usefulness and perceived ease of use to explain the variation in the dependent variable, intention to adopt cloud computing. The findings of the study suggested that relative advantage, compatibility, complexity, organizational readiness, top management commitment, and training and education were the most important variables affecting the adoption.
3. Research Model and Hypotheses
The main objective of this study is to investigate the influence of TOE elements on the Intention of organizations to adopt cloud computing. Therefore, the variable of primary interest is the “Intention to adopt cloud computing”, which is the dependent variable, and Technological, Organizational, and Environmental factors are the independent variables used to explain the variance in the dependent variable. Research Model is represented in Figure 1.
Figure 1. Research model. Technological, Organizational and Environmental (TOE) model.
Based on the objective of this study as well as the study’s research model, the following hypotheses are developed and will be tested:
H1: Technology factor does not influence the intention to Adopt Cloud Computing.
H2: Organizational factor does not influence the intention to Adopt Cloud Computing.
H3: Environmental factor does not influence the intention to Adopt Cloud Computing.
4. Research Methodology
In order to evaluate how Technological, Organizational and Environmental factors affect the cloud computing adoption decision, a quantitative research will be conducted, where data will be collected through a questionnaire, which will attempt to help hospitals gain a better understanding about how these three factors affect their decision to adopt and deploy a cloud computing model.
The population of the study consisted of 47 hospitals that operate in the Jordanian healthcare sector. 223 questionnaires were distributed to the employees working in the IT department in hospitals located in the capital of Jordan, Amman. The hospitals were selected randomly based on Uma Sekaran sampling method, employees’ were be chosen from each of our randomly selected hospitals to represent the sample used in this research  .
Three factors that affect the decision to adopt cloud computing will be measured through 8 variables; Technological factor which includes 3 items; relative advantage, complexity and compatibility as suggested by reference  , Environmental factor includes 3 items; where competitive pressure, trading partner pressure are also derived from  and supplier scarcity is derived from a study conducted by reference  . Finally, Organizational factor that includes 2 items; top management support and technology readiness are also derived from  . Cloud computing adoption was measured through 3 items based on a study conducted by  .
In order to investigate the hypotheses associated with this research, the collected data will help examine the relationship between the variables of interest to the study. The data were analyzed using Statistical Package for Social Sciences (SPSS) version 19. A measure of multiple regression analysis will be conducted, in addition to reliability and multicollinearity tests. The results will provide the foundation for accepting or rejecting the hypotheses and answering the research question.
5. Data Analysis and Results
In order to examine the effect of TOE research Model on the intention to adopt cloud computing, 5 points Likert scale systems were used. Scale varies between strongly disagree = 1 and strongly agree = 5. Reliability and validity analyses were conducted, in addition to multi co-linearity test. Also multiple regression analysis was conducted to test the research hypothesis.
5.1. Validity and Reliability
Validity and reliability are two important measures that determine the quality and usefulness of the data collected. Validity is about accuracy and whether the instrument measures what it is intended to measure. Reliability is about precision; it is used to check the consistency and stability of the questionnaire. The researchers of the current study depended on scales and items that were previously developed and used by other researchers with similar interests. In addition, a draft of the questionnaire was reviewed by four academic lecturers?who have sufficient knowledge and experience in this scope to make sure that each item is measuring what is expected to measure, and to avoid any ambiguity or complexity in the phrasing of the questions. The reliability of the instrument was measured by the Cronbach’s alpha coefficient. According to  , the values of all indicators or dimensional scales should be above the recommended value of 0.60. Table 1 represents the results of Cranach’s alpha for the independent and dependent variables. Cronbach’s alpha coefficients of all the tested variables are above 0.60 which indicates that the composite measure is reliable.
5.2. Hypotheses Testing Results
The objective of this research is to investigate the effect of TOE framework (Technology, Organizational, Environmental factors) on the Intention of Hospital in Jordan to adopt cloud computing. Consequently, in order to test the hypotheses developed for this study, multiple regression technique was used. Further, the level of significance (α-level) was chosen to be 0.05 and the probability value (p-value) obtained from the statistical hypotheses test is considered to be the decision rule for rejecting the null hypotheses  . If the p-value is less than or equal to α-level, the null hypothesis will be rejected and the alternative hypothesis will be supported. However, if the p-value is greater than the α-level, the null hypothesis cannot be rejected and the alternative hypothesis will not be supported. In addition, normality of the independent variables and the absence of multi co-linearity problem (a case of multiple regression in which the independent variables are themselves highly correlated) were checked. As suggested by  , most of the values should be inside the adequate ranges for normality. For this purpose, tolerance and Variance Inflation Factor (VIF) were investigated; a VIF value of 5 or 10 and above and a tolerance of less than 0.20 indicate that variables are multicollinear. Table 2 shows the results.
From the above table, it can be seen that VIF ranges between 1.407 and 1.565 which are well-below five. In addition, the tolerance values range between 0.639 and 0.711 which are above 0.2. These factors indicate that there is no evidence of multicollinearity problem in the regression model. In addition to the VIF and tolerance values, Pearson Correlation Matrix was computed for the independent variable dimensions to check correlation between them (Table 3).
According to  , a value of 0.75 and above suggests high correlation between the variables. The results in the above table, are all below 0.75 and thus don’t suggest high correlation between the variables. Therefore, these findings also show that there is no evidence of multicollinearity problem.
The results of testing the three hypotheses regarding the effect of TOE framework on the intention to adopt cloud computing are presented in Table 4.
As indicated in Table 4, there is a positive correlation between TOE framework and the intention to adopt cloud computing since the multiple correlation coefficient r = 0.431. The adjusted R2 relates to the generalisability of the model. It allows us to generalize the results taken from the respondents to the whole population. In this case it equals 0.186. The results showed that F-ratio for these data is equal to 16.633, which is statistically significant at p < 0.05. Therefore, we conclude that there is a statistically significant effect of TOE framework on the intention to adopt cloud computing.
The β indicates to the individual contribution of each predictor (independent variable) to the model, if other predictors are held constant. Table 4 shows the standardized coefficients for each TOE framework dimension.
Table 1. The study variables’ Cronbach’s alpha.
Table 2. Tolerance and VIF for the independent variables.
Table 3. Pearson correlation matrix.
Table 4. Result for the study model (b).
aPredictors: (Constant), Technology factor, Organizational factor, Environment factor; bDependent variable: Intention to adopt cloud computing.
The values of β for Technology factor, Organizational factor, and Environmental factor are 0.211, 0.113, 0.207 respectively, which are all positive. The level of effect of these variables depends on the β value, the higher β value the higher the effect on the dependent variable. It can be concluded from the values of beta that the variable that has the highest contribution in the model is Technology factor, followed by Environmental factor and finally the Organizational factor.
6. Discussion and Conclusion
The main purpose of conducting this research was to determine whether the factors suggested by the TOE framework influenced the intention of hospitals to adopt a new innovation like cloud computing, particularly in the country of Jordan where healthcare sector cared tremendously about any new breakthroughs in technology that might aid in the improvement of healthcare services provided. The results of the study indicated that the three factors proposed by the framework (Technology, Organization, and Environment) played a role in the decision to adopt cloud computing in Jordanian hospitals.
The first hypothesis of this study states that “Technology factor does not influence the intention to Adopt Cloud Computing”. This hypothesis was rejected; it was found that the Technology had a positive significant impact on the intention to adopt cloud computing. Moreover it was found that this factor had the most impact on the decision of adopting this new innovation. This result supports the findings of other researchers such as      . This may be attributed to the dimensions of the technology factor, where it has been suggested that when firms perceive a relative advantage from an innovation, they are likely to adopt it  . The technology of cloud computing has different benefits such as reduced cost, mobility, flexibility and resources sharing  . Cloud computing services can make organizations more effective  . Organizations require confirmation that substantive benefits from cloud computing are feasible before its adoption can be considered. This could be important particularly when spending on such technology is constrained by limited budgets  . Moreover, complexity plays an important part in cloud computing adoption. Many organizations have some concerns and fears about investing in new IT innovations. Compatibility is another reason why technology is an important factor to take into consideration when adopting cloud computing. It is crucial to understand if the technology is compatible with the current infrastructures in the organization and if the technology is compatible with current values and needs of adopters  . Cloud computing must be compatible with companies’ policy, IT development environment, and business needs  . Therefore, steps must be taken to change existing processes to meet compatibility of cloud solutions in the organization’s infrastructure. However, researchers such as  and  stated that compatibility was not considered and crucial motivational for cloud computing adoption. This disagrees with the findings of this study.
This study attempts to test the suggested adoption model presented in Figure 1 (TOE model). Results of this research proved that the three factors of this framework (Technology, Organization and Environment) are connected to each other and significantly influence the decision of organizations, particularly hospitals, to adopt cloud computing. The factor that influenced the intention to adopt cloud computing the most was the Technological factor followed by the Environmental factor, and finally the Organizational factor. The findings of this research are critical to ICT managers as well as providers. Findings can help in developing plans for cloud computing adoption. For ICT service providers, the research model can help them to understand clearly how and why hospitals in Jordan choose to adopt cloud computing services. In addition, organizations can assess whether services are in fact compatible with their systems and how complex is the service to implement and understand.
Future research can use this study as a base to build on in an effort to adopt better cloud computing in other sectors as well. In this study a structured questionnaire was used to collect data regarding the influence of the TOE framework on the intention of hospitals to adopt cloud computing. Although this approach is useful in understanding business-related decisions, it may not be able to reflect the exact reason behind the intention of decision makers to adopt or overlook cloud computing. Furthermore, the study was undertaken in the country of Jordan where not many organizations, particularly hospitals, have heard of let alone attempted to adopt cloud computing so further studies need to be conducted in order to be able to generalize the results obtained in this study.
 Misra, S.C. and Mondal, A. (2011) Identification of a Company’s Suitability for the Adoption of Cloud Computing and Modeling Its Corresponding Return on Investment. Mathematical and Computer Modelling, 53, 504-521.
 Sultan, N. (2010) Cloud Computing for Education: A New Dawn? International Journal of Information Management, 30, 109-116.
 Demirkan, H., Kauffman, R.J., Vayghan, J.A., Fill, H., Karagiannis, D. and Maglio, P.P. (2008) Service-Oriented Technology and Management: Perspectives on Research and Practice for the Coming Decade. Electronic Commerce Research and Applications, 7, 356-376.
 Owunwanne, D. and Goel, R. (2010) Radio Frequency Identification (RFID) Technology: Gaining A Competitive Value through Cloud Computing. International Journal of Management and Information Systems, 14, 157-164.
 Swash, G. (1998) UK Business Information on the Internet. New Library World, 99, 238-242.
 Bayo-Moriones, A. and Lera-Lo′pez, F. (2007) A Firm-Level Analysis of Determinants of ICT Adoption in Spain. Technovation, 27, 352-366.
 Dwivedi, Y.K. and Mustafee, N. (2010) It’s Unwritten in the Cloud: The Technology Enablers for Realising the Promise of Cloud Computing. Journal of Enterprise Information Management, 23, 673-679.
 Choudhary, V. and Vithayathil, J. (2013) The Impact of Cloud Computing: Should the IT Department be Organized as Cost Centre or a Profit Center? Journal of Management Information Systems, 30, 67-100.
 11 Oliveira, T., Thomas, M. and Espadanal, M. (2014) Assessing the Determinants of Cloud Computing Adoption: An Analysis of the Manufacturing and Services Sectors. Information and Management, 51, 497-510.
 Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., et al. (2010) A View of Cloud Computing. Communications of the ACM, 53, 50-58.
 Goscinski, A. and Brock, M. (2010) Toward Dynamic and Attribute Based Publication, Discovery and Selection for Cloud Computing. Future Generation Computer Systems, 26, 947-970.
 Tuncay, E. (2010) Effective Use of Cloud Computing in Educational Institutions. Proscenia-Social and Behavioral Sciences, 2, 938-942.
 Mell, P. and Grance, T. (2011) The NIST Definition of Cloud Computing, Computer Security Division Information Technology Laboratory National Institute of Standards and Technology, Gaithersburg, MD.
 Rohani, M.B. and Hussin, R.C. (2015) An Integrated Theoretical Framework for Cloud Computing Adoption by Universities Technology Transfer Offices (TTOs). Journal of Theoretical and Applied Information Technology, 79, 415-430.
 Pyke, J. (2009) Now Is the Time to Take the Cloud Seriously. White Paper.
 Low, C., Chen, Y. and Wu, M. (2011) Understanding the Determinants of Cloud Computing Adoption. Industrial Management & Data Systems, 111, 1006-1023.
 Private Hospitals Association (2015).
 Rawabdeh, A. (2007) An E-Health Trend Plan for the Jordanian Health Care System: A Review. International Journal of Health Care Quality Assurance, 20, 516-531.
 Lin, A. and Chen, N. (2012) Cloud Computing as an Innovation: Perception, Attitude, and Adoption. International Journal of Information Management, 32, 533-540.
 Lian, J.W., Yen, D.C. and Wang, Y.T. (2014) An Exploratory Study to Understand the Critical Factors Affecting the Decision to Adopt Cloud Computing in Taiwan Hospital. International Journal of Information Management, 34, 28-36. http://dx.doi.org/10.1016/j.ijinfomgt.2013.09.004
 Saya, S., Pee, L.G. and Kankanhalli, A. (2010) The Impact of Instutational Influences on Perceived Technological Characteristics and Real Options in Cloud Computing Adoption. Proceedings of the 31st International Conference on Information Systems, St. Louis, January 2010.
 Rochwerger, B., Breitgand, D., Levy, E., Galis, A., Nagin, K., Llorente, I. and Galan, F. (2009) The Reservoir Model and Architecture for Open Federated Cloud Computing. IBM Journal of Research and Development, 53, 1-11.
 Liu, H. and Orban, D. (2008) GridBatch: Cloud Computing for Large-Scale Data-Intensive Batch Applications. Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid, Lyon, 19-22 May 2008, 295-305.
 Assuncao, M.D., Costanzo, A. and Buyya, R. (2009) Evaluating the Cost-Benefit of Using Cloud Computing to Extend the Capacity of Clusters. Proceedings of the 18th ACM International Symposium on High Performance Distributed Computing, Munich, 11-13 June 2009, 141-150.
 Marston, S., Li, Z., Bandyopadhyay, S., Juheng, Z. and Anand, G. (2011) Cloud Computing—The Business Perspective. Decision Support Systems, 51, 176-189.
 Buyya, R., Yeo, C.S., Venugopa, S., Broberg, J. and Brandic, I. (2009) Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. Future Generation Computer Systems, 25, 599-616.
 Noor, T., Sheng, Z., Zeadally, S. and Yu, J. (2013) Trust Management of Services in Cloud Environments: Obstacles and Solutions. ACM Computing Surveys, 46, 12-30.
 Erdogmus, H. (2009) Cloud Computing: Does Nirvana Hide behind the Nebula? IEEE Software, 26, 4-6.
 Hayes, B. (2008) Cloud Computing. Communications of the ACM, 51, 9-11.
 Ercan, T. (2010) Effective Use of Cloud Computing in Educational Institutions. Procedia-Social and Behavioral Sciences, 2, 938-942.
 Thomas, P.Y. (2011) Cloud Computing: A Potential Paradigm for Practising the Scholarship of Teaching and Learning. The Electronic Library, 29, 214-224.
 Gangwar, H., Date, H. and Ramaswamy, R. (2015) Understanding Determinants of Cloud Computing Adoption Using an Integrated TAM-TOE Model. Journal of Enterprise Information Management, 28, 107-130.
 Sultan, N. (2011) Reaching for the “Cloud”: How SMEs Can Manage. International Journal of Information Management, 31, 272-278.
 Yang, S. (2012) Move into the Cloud, Shall We? Library Hi Tech News, 29, 4-7.
 Zhu, K., Kraemer, K.L., Xu, S. and Dedrick, J. (2004) Information Technology Payoff in E-Business Environments: An International Perspective on Value Creation of E-Business in the Financial Services Industry. Journal of Management Information Systems, 21, 17-54.
 Swanson, E.B. (1995) Information Systems Management among Organizations. Management Science, 40, 1069-1092.
 Alshamaila, Y., Papagiannidis, S. and Li, F. (2013) Cloud Computing Adoption by SMEs in the North East of England: A Multi-Perspective Framework. Journal of Enterprise Information Management, 26, 250-275.
 Awa, H. O., Ukoha, O., Bartholomew, O. and Emecheta, C. (2015) Integrating TAM, TPB and TOE Frameworks and Expanding Their Characteristic Constructs for E-Commerce Adoption by SMEs. Journal of Science & Technology Policy Management, 6, 76-94.
 Premkumar, G. (2003) A Meta-Analysis of Research on Information Technology Implementation in Small Business. Journal of Organizational Computing and Electronic Commerce, 13, 91-121.
 To, M. and Ngai, E. (2006) Predicting the Organisational Adoption of B2C E-Commerce: An Empirical Study. Industrial Management and Data Systems, 106, 1133-1147.
 Gutierrez, A., Boukrami, E. and Lumsden, R. (2015) Technological, Organisational and Environmental Factors Influencing Managers’ Decision to Adopt Cloud Computing in the UK. Journal of Enterprise Information Management, 28, 788-807.
 Feuerlicht, G. and Govardhan, S. (2010) Impact of Cloud Computing: Beyond a Technology Trend. Proceedings of the International Conference on Systems Integration, Oeconomica, Prague, 8-9 June 2010, 1-8.
 Sonnenwald, D.H., Maglaughlin, K.L. and Whitton, M.C. (2001) Using Innovation Diffusion Theory to Guide Collaboration Technology Evaluation. Proceedings of the IEEE 10th International Workshop on Enabling Technologies, Work in Progress, Infrastructure for Collaborative Enterprises, Cambridge, 20-22 June 2001, 114-119.
 Sahin, I. (2006) Detailed Review of Rogers’ Diffusion of Innovations Theory and Educational Technology-Related Studies Based on Rogers’ Theory. The Turkish Online Journal of Educational Technology, 5, 14-23.
 Berman, S., Kesterson-Townes, A. and Marchal, A. (2012) How Cloud Computing Enables Process and Business Model Innovation. Strategy and Leadership, 40, 27-35.
 Peng, R., Xiong, L. and Yang, Z. (2012) Exploring Tourist Adoption of Tourism Mobile Payment: An Empirical Analysis. Journal of Theoretical and Applied Electronic Commerce Research, 7, 21-33.
 Lin, H.F. and Lin, S.M. (2008) Determinants of E-Business Diffusion: A Test of the Technology Diffusion Perspective. Technovation, 28, 135-145.
 Wang, Y., Wang, Y. and Yang, Y. (2010) Understanding the Determinants of RFID Adoption in the Manufacturing Industry. Technological Forecasting & Social Change, 77, 803-815.
 Parasuraman, A. (2000) Technology Readiness Index (Tri): A Multiple-Item Scale to Measure Readiness to Embrace New Technologies. Journal of Service Research, 2, 307-320.
 Laforet, S. (2011) A Framework of Organisational Innovation and Outcomes in SMEs. International Journal of Entrepreneurial Behaviour and Research, 17, 380-408.
 Ramdani, B., Kawalek, P. and Lorenzo, O. (2009) Predicting SMEs’ Adoption of Enterprise Systems. Journal of Enterprise Information Management, 22, 10-24.
 Li, M., Zhao, D. and Yu, Y. (2015) TOE Drivers for Cloud Transformation: Direct or Trust-Mediated? Asia Pacific Journal of Marketing and Logistics, 27, 226-248.
 Cegielski, C.G., Farmer, L.A., Wu, Y. and Hazen, B.T. (2012) Adoption of Cloud Computing Technologies in Supply Chains. The International Journal of Logistics Management, 23, 184-211.
 Alkhater, N., Wills, G. and Walters, R. (2014) Factors Influencing an Organisation’s Intention to Adopt Cloud Computing in Saudi Arabia. Proceedings of the IEEE 6th International Conference on Cloud Computing Technology and Science, Singapore, 15-18 December 2014, 1040-1044.
 Teo, T.S.H., Lin, S. and Lai, K.H. (2009) Adopters and Non-Adopters of E-Procurement in Singapore: An Empirical Study. Omega, 37, 972-987.
 Kim, B. and Lee, S. (2008) Factors Affecting the Implementation of Electronic Data Interchange in Korea. Computers in Human Behavior, 24, 263-283.
 Lertwongsatien, C. and Wongpinunwatana, N. (2003) E-Commerce Adoption in Thailand: An Empirical Study of Small and Medium Enterprises (SMEs). Journal of Global Information Technology Management, 6, 67-83.
 Ramdani, B. and Kawalek, P. (2007) SME Adoption of Enterprise Systems in the Northwest of England: An Environmental, Technological and Organizational Perspective. In McMaster, T., Wastell, D., Ferneley, E. and DeGross, J.I., Eds., Organizational Dynamics of Technology-Based Innovation: Diversifying the Research Agenda, Springer, Boston, 409-429.
 Chong, A.Y.L. and Ooi, K.B. (2008) Adoption of Interorganizational System Standards in Supply Chains: An Empirical Analysis of RosettaNet Standards. Industrial Management & Data Systems, 108, 529-547.
 Zhu, K., Dong, S., Xu, S. and Kraemer, K. (2006) Innovation Diffusion in Global Contexts: Determinants of Post-Adoption Digital Transformation of European Companies. European Journal of Information Systems, 15, 601-616.