Technology Trade Theory (TripleT)

Doctoral Thesis / Dissertation, 2013

169 Pages, Grade: 3.87/4.00



1.1. Problem Statement
1.2. Background/Introduction-Technology Acceptance and Cloud Computing 11Error! Bookmark not defined
1.3. Research Objectives
1.4. Research Questions
1.5. Significance of Research
1.6. Organization of Research

2.1. Empirical Research in Cloud Computing Technology
2.1.1. Definition of Cloud Computing
2.1.2. Characteristics of Cloud Computing
2.1.3. Cloud Computing Technology
2.1.4. Service Models
2.1.5. Deployment Models
2.1.6. How Cloud Computing Works
2.1.7. Cloud Computing Applications
2.1.8. Advantages of Cloud Computing
2.1.9. Disadvantages of Cloud Computing
2.1.10. Gaps in Cloud Computing Literature
2.2. Empirical Research in Relevant Disciplines: Theories of Technology Adoption
2.2.1. Theory of Reasoned Action
2.2.2. Theory of Planned Behavior
2.2.3. Technology Acceptance Model
2.2.4. TAM2
2.2.5. Decomposed Theory of Planned Behavior (decomposed TPB)
2.2.6. Motivational Model
2.2.7. The Model of PC Utilization
2.2.8. The Innovation Diffusion Theory
2.2.9. The Unified Theory of Acceptance and Use of Technology (UTAUT)
2.2.10. Social Exchange Theory (SET)
2.2.11. Gaps in Technology Acceptance Model Literature

3.1. Theoretical Framework
3.1.1. The Proposed Model
3.1.2. Research Hypothesis / Questions
3.1.3. Operational Definitions of Variables
3.1.4. Rival Hypothesis
3.1.5. Plausibility Assessment of Rival Hypotheses
3.2. Research Design Approach
3.3. Context of Study
3.3.1. Setting
3.3.2. Population
3.3.3. Limitations
3.3.4. Sample Design and Selection
3.4. Feasibility Analysis and Design Selection
3.4.1. Data Collection
3.4.2. Methods of Measurement
3.4.3. Instrumentation
3.4.4. Data Collection Procedures
3.4.5. Data Coding
3.4.6. Data Collected
3.4.7. Data Quality Assessment

4.1. Data analysis
4.1.1. Data Analysis Procedures
4.1.2. Data Analysis Methods
4.2. Results
4.2.1. Demographic Characteristics of the Respondents
4.2.2. Cross Tabulation of Results
4.2.3. Analysis of Relationships in TAM Framework
4.2.4. Hypotheses Testing

5.1. Contribution to Knowledge
5.2. Implication for Future Research
5.3. Implication for Practitioners
5.4. Implication for Policy Makers
5.5. Conclusions




Figure 1: How Cloud Computing Works

Figure 2: Number of technology adoption studies

Figure 3: The Theory of Reasoned Action

Figure 4: The Theory of Planned Behavior

Figure 5: Conceptual Design of the Technology Acceptance Model

Figure 6: The Generic TAM Model

Figure 7: The TAM Model

Figure 8: The TAM2 Model

Figure 9: TAM 2 Model

Figure 10: DTPB

Figure 11: DTPB

Figure 12: Motivational model

Figure 13: Refined SDT Model

Figure 14: Model of PC Utilization

Figure 15: Innovation Diffusion Theory

Figure 16: The Unified Theory of Acceptance and Use of Technology (UTAUT)

Figure 17: the SET theory

Figure 18: The Proposed T3 Model

Figure 19: The Deductive Approach

Figure 20: Cost Savings and Cloud Computing

Figure 21: Time Savings and Cloud Computing Adoption

Figure 22: Space Savings and Cloud Computing Adoption

Figure 23: Automation and Cloud Computing Adoption

Figure 24: Remote Implementation and Cloud Computing Adoption

Figure 25: Scalability and Cloud Computing Adoption

Figure 26: Flexibility and Cloud Computing Adoption

Figure 27: Business Mobility and Cloud Computing Adoption

Figure 28: Remote Implementation and Cloud Computing Adoption

Figure 30: Privacy Infringement and Cloud Computing Adoption

Figure 31: Intermittency and Cloud Computing Adoption

Figure 32: Patriot Act and Cloud Computing Adoption

Figure 33: Loss of Control and Cloud Computing Adoption

Figure 34: Loss of Control and Cloud Computing Adoption

Figure 35: Loss of Control and Cloud Computing Adoption

Figure 36: TAM model


Table 1: Applications of Cloud Computing

Table 2: Key Focus Areas for Cloud Computing Studies

Table 3: Contradictory Relationships between TAM Variables

Table 4: Summary of Some Survey Studies

Table 5: Respondents Profile

Table 6: The Relationship between Perceived Advantages and Behavioral Intentions

Table 7: Perceived Disadvantages and Behavioral Intentions

Table 8: Behavioral Intentions and Actual Behavioral Performance

Table 9: Cost Savings and Cloud Computing

Table 10: Time Savings and Cloud Computing Adoption

Table 11: Space Savings and Cloud Computing Adoption

Table 13: Remote Implementation and Cloud Computing Adoption

Table 14: Scalability and Cloud Computing Adoption

Table 15: Flexibility and Cloud Computing Adoption

Table 16: Business Mobility and Cloud Computing Adoption

Table 17: Security Risks and Cloud Computing Adoption

Table 19: Privacy Infringement and Cloud Computing Adoption

Table 21: Patriot Act and Cloud Computing Adoption

Table 22: Loss of Control and Cloud Computing Adoption

Table 23: Lack of Standards and Cloud Computing Adoption

Table 24: Data Loss and Cloud Computing Adoption

Table 25: Adoption Intentions

Table 26: Actual Adoption

Table 27: Cronbach’s Alpha

Table 28: Descriptive Statistics

Table 29: Descriptive Statistics

Table 30: Demographic Characteristics of the Respondents

Table 31: Pearson’s r for the Advantages

Table 32: Pearson’s r for the Disadvantages

Table 33: Adoption Intentions and Actual Behavioral Performance

Table 34: Advantages: Scoring and Weighting

Table 35: ƩwiAi

Table 36: Disadvantages: Weighting and Scoring

Table 37: ƩwiDi:


Even though cloud computing is one of the hottest growth areas in the field of IT today, the existing body of literature related to cloud computing remains surprisingly small. The few research studies extant in the area have primarily focused on two broad areas, including: the technical implications of implementing cloud computing solutions, and the impact of cloud computing adoption by individual and organizational users. The behavioral aspects of cloud computing adoption, and especially using adoption models as a theoretical basis, remain least studied and most misunderstood. Moreover, existing models have been tested and used to gauge the behavior intention to adopt technology from a single perspective.

Accordingly, this study proposes a new model for evaluating technology adoption, with specific reference to cloud computing adoption - the Technology Trade Theory (or Triple- T) model. This model is derived from the synthesis of the Technology Acceptance Model and the Social Exchange Theory. The Triple T model proposes that technology acceptance is the result of a trade process. The purpose of this trade is to maximize advantages and minimize disadvantages. Prospective adopters will weigh the potential advantages and disadvantages of the technology and will only adopt the technology when its advantages outweigh its disadvantages.

Data is collected using a panel study administered to a sample of middle and top level IT managers. Relationships between the variables are assessed using the Pearson product moment correlation coefficient. Significance is tested by means of paired two-tailed tests.

Even though the study validates most of the relationships between variables in the TAM model, it still finds that the TAM model has less predictive ability. Since the proposed Triple T model addresses many of the weaknesses in the TAM model, the study proposes it to be a better model.

The proposed Triple T model also finds that a single advantage may outweigh numerous disadvantages or that a single disadvantage may outweigh numerous advantages during the adoption process and therefore executive decisions to adopt technology are often driven by just one advantage or disadvantage to the exclusion of all the others.

These findings suggest that substantial improvement in the prediction of technology adoption intention is possible when previous models are integrated with the Social Exchange Theory. The implications of the findings to practitioners and policymakers are discussed and future research directions given.



For guidance; we could not possibly be guided, if it were not that Allah has guided us. Praise be to Allah who taught by the pen. Praise be to Allah who taught man what he did not know. Praise be to Allah who has allowed things whose advantages outweigh disadvantages and Has forbidden things whose disadvantages outweigh advantages. Praise be to Allah who granted me success in completing this dissertation


For guidance; he guided us to the Straight Path of Islam with the Qur’an and Hadith as our guides; and the best guidance is the guidance of Prophet Mohammad; He said “Actions are but by intentions”. May the blessings and peace of Allah be upon him

To my parents

Ammonih and AbdulQadir

For their love, care, endurance, and prayers

To my wife


For her wisdom, endurance, and encouragement

To my kids

Mahdy, Dara and Dali

For their love, sympathy, and support

To my brothers and sisters with special node goes to Mo’tasim For his persistent support


I would like to express heartfelt appreciation to my research advisor, Prof. Dr. Tayfun Turgay, who had a profound impact upon not only my career, but also my life. He taught me that if you understand the logic of what you are trying to solve, then the syntax is the least significant part of the equation. I am forever grateful to him for forcing his students to figure out problems on their own, instead of spoon-feeding us the steps to solving problems. I am truly indebted to professor Turgay for enabling me to overcome the challenges and made himself available throughout the process without hesitation.

I also would like to express gratitude to my dissertation committee, Professor Tayfun Turgay, Professor Alexander Kostin, Professor Serdar Saydam and Dr. Yasemin Fanaeian.

I wish to express my deep and heartfelt gratitude to the faculty members at The American University of Cyprus: Drs, Tayfun Turgay, Alexander Kostin, Serdar Saydam, Beran Necat, Ali Hayder, Suleyman Goker and Figen Yesilada for their interest and support.

I would also like to acknowledge all administrative staff at The American University of Cyprus, with special node goes to Ms. Elvira Sabirova, head of International Marketing Office; for her kind and prompt responses during the lengthy journey; at all stages she wasn’t waivered to answer all my inquiries.

I would be remiss if I did not acknowledge my brother and friend Mo’tasim A. Obeidat, the director of Almafraq Court at Jordan; this dissertation could not have been completed without his support and encouragement.

Furthermore, special gratitude goes to each and everyone who helped me during the lengthy research. I would also like to acknowledge everyone who have been supportive and happy for me on this journey to complete my mission with success.

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Some advantages to people but their

Disadvantages Outweigh Their Advantages



1.1. Problem Statement

The technology acceptance model (TAM) is the most commonly used model for explaining technology adoption behavior, this notwithstanding the fact that it has been associated with fundamental weaknesses which blunt its robustness and predictive ability. Technological advances such as autonomic computing and virtualization have led to the emergence of cloud computing which promises significant benefits for businesses which adopt this technology, necessitating the need for a better way for understanding the technological adoption process in order to ensure that business organizations reap the benefits associated with cloud computing.

1.2. Background/Introduction-Technology Acceptance and Cloud Computing

Technology adoption has long been touted as a major enabler of organizational success. At the strategic level, technology adoption is widely accepted as a major driver of cost reductions, productivity improvements, more effective communication, higher quality products, increased business process efficiencies, and market expansion, among other many benefits (David, Agboh, & Radhakrishnan, 2010; Teo & Ranganathan, 2004).

In spite of the potential benefits which the adoption of IT offers, and perhaps because of the perceived attendant risks, there is striking unanimity in the technological adoption discourse that many organizations do not adopt new technology as intensely as others do. Against this background, the growth in the number of empirical studies focusing on technological adoption has been nothing short of dramatic. These studies have focused on a wide array of technologies, including: information technology (David, Agboh, & Radhakrishnan, 2010), clean technology (González, 2005), insect management technology (Harper et al, 1990), dust-removing technology (Ning, 1997), biometric security systems (Lease, 2005), among many others.

Within the Information Technology (IT) sphere, a number of studies have focused on specific areas, some of which include:

- E-mail adoption (for example, Szajna, 1996; Adams et al, 1992; Gefen and Straub, 1997).
- The internet (for example, Teo et al, 1999).
- The adoption of word processing or spread sheet applications (for example, Chau, 1996; Hendrickson & Collins, 1996; Mathieson, 1991).
- The adoption of the microcomputer (for example Igbaria et al, 1997).
- The adoption of internet browsers (for example Morris & Dillon, 1997).
- The adoption of data management applications (Rotini, 2011).

In the last few years, advances in IT have led to the emergence of entirely new technologies such as virtualization, parallel computing, and autonomic computing, inter alia. Backed by the innovation of new business models such as the pay-as-you-go model, these have spawned the emergence of cloud computing, which has been defined by McDonald, McDonald, & Breslin (2009, p.5) as the “delivery of elastic computing resources over the internet by external service providers.”

Even though there has been a dramatic increase in the number of studies focusing on the adoption of technology in general, and of information technology in particular, significantly less attention has been paid to cloud computing with the few notable studies in this regard including those of Shimba (2010), Jlelaty & Monzer (2012), and Low, Chen & Wu (2011). It is against this background that this study aims at evaluating the adoption of technology, with specific reference to cloud computing.

Scholars and practitioners have researched and are still analyzing the factors that influence technology acceptance. Theories and models developed by scholars in this field have tended to focus on the factors that influence technology acceptance and have rarely weighed them. Most studies have tended to gauge the effect of each single variable rather than weighing and modeling it systematically. Technology Trade Theory (Triple T or T3), the unified theoretical framework which this study proposes, is a comprehensive and more powerful in describing and predicting consumer adoption of technology and therefore goes a long way in bridging this gap.

1.3. Research Objectives

The purpose of this research is to develop and empirically test a unified theory of technology acceptance. More specifically, the primary objective is to incorporate the well-known Social Exchange Theory (SET) into the Technology Acceptance Model (TAM) (Davis, 1989), the most popular model used for predicting technology adoption. An additional goal is to improve the conceptualization of perception by identifying and categorizing all technology related features and capabilities into two main categories advantages and disadvantages. Additionally, the study aims at testing the proposed model to answer the main research question: Do advantages of cloud computing initiatives outweigh its disadvantages? Another major goal of the study is to analyze the adoption intention and finally the actual adoption of technology, in the process demonstrating that this unified theoretical framework, the Technology Trade Theory (Triple-T), is comprehensive and more powerful in describing and predicting consumer adoption of technology.

1.4. Research Questions

Based on the research aims and objectives as explained in the preceding sub-section, the following research questions will guide this study:

- What are the advantages and disadvantages of cloud computing?
- Do the advantages of cloud computing outweigh its disadvantages?

1.5. Significance of Research

The technology acceptance model (TAM) has been widely recognized as the most popular model for explaining technology, and one which has therefore received the highest number of citations in technology adoption literature (Li, 2011; Chuttur, 2009; Lee, Kozar & Larsen, 2003). This has been attributed to its intuitive appeal and simplicity in use and implementation. Notwithstanding this, successive empirical studies have established that this model suffers from several fundamental weaknesses, which attenuate its predictive ability, relevance, and usefulness as a technology adoption model. By conceptualizing and operationalizing the Technology Trade Theory (Triple-T), this study offers an alternative to the TAM. Addressing the inherent weaknesses of the TAM as it does, the study offers a more robust model for understanding technology adoption as well as a framework with a higher predictive capability.

By integrating elements of the social exchange theory into the generic TAM, it acknowledges that business organizations are profit-maximizing entities whose decisions are grounded on a utilitarian rather than deontological perspective, and therefore elevates the place of the cost-benefit matrix in the behavioral performance equation. This model therefore carries a lot of significance for business organizations. It also has fundamental and weighty implications for theory.

By offering a more robust model for the analysis of technology adoption, and one that also has a higher predictive ability than the ubiquitous TAM; this study will facilitate a more accurate and richer understanding of the adoption process, and will help accelerate the diffusion of technologies such as cloud computing technology, allowing organizations to reap the benefits associated with technological adoption. These include: cost improvements, efficiency and productivity enhancements, and better communication, among others. The study’s results may also help cloud computing developers, vendors, and marketers understand the important perceptions of cloud computing technology within their customer base of IT executives.

Among other implications of theoretical significance, it questions the role of affect in technology adoption, and introduces the aspect of weighting in the consideration of the features which motivate the behavioral intentions of those required to make the adoption decision.

1.6. Organization of Research

The next section of the study, the literature review, forms the second chapter of this study. This chapter is divided into two sections. In the first section, a review of the cloud computing literature is undertaken. More specifically, various definitions of cloud computing as given by different authorities are considered, on the basis of which a standard definition synthesizing all the essential elements is given. The characteristics of cloud computing are also reviewed. Other issues reviewed include the technology underpinning the cloud computing concept, service models commonly deployed in cloud computing, the deployment models of cloud computing, how cloud computing works, and the applications of cloud computing. The advantages and disadvantages of cloud computing are also discussed, before gaps in the cloud computing literature are adduced. In the second section of Chapter 2, a critical review of the theories which motivate adoption behavior is undertaken. The theories reviewed include: the theory of reasoned action, the theory of planned behavior, the decomposed theory of planned behavior, the technology acceptance model. TAM2, the motivational model, the model of PC utilization, the innovation diffusion theory, the social cognitive model, the unified theory of acceptance and use of technology, and the social exchange theory. On the basis of this review, the gaps relating to the literature on technology adoption are identified and the next steps taken.

The next section of the study, Chapter 3, is the methodology section. This lays out the methods, processes, instruments, and procedures used in the study to achieve the research objectives. In Chapter 3, the theoretical framework of the study is first presented. Among other things, this clarifies the proposed model, the research questions and hypotheses, the operational definition of the variables, and the rival hypotheses. An assessment of the plausibility of the rival hypotheses is also undertaken. Having laid out the theoretical framework of the study, the research design adopted by the researcher is given. The context of the study, encompassing elements such as the setting, the population, sample design and selection, and the research limitations is next enumerated. The feasibility analysis, data collection methods, measurement methods, instrumentation, and the assessment of data quality are also discussed at length.

The methodology section is followed by the presentation of the results and findings, which forms Chapter 4 of the study. The data collected is analyzed using several positivistic techniques, and the hypotheses adduced earlier on in the study are tested, after which the findings are presented.

Chapter 5 is the last section of this study. Based on the findings presented in Chapter 4, Chapter 5 draws the necessary inferences regarding the adoption of cloud computing technology. The implications of these findings are also discussed. Chapter 5 also discusses the study’s contributions to knowledge, directions for future research, and the implications for practitioners and policy makers.


2.1. Empirical Research in Cloud Computing Technology

This section reviews the literature which is extant in the computing technology field. It reviews the various definitions of cloud computing before synthesizing them and offering a standard definition. It also reviews the characteristics of cloud computing technology, the technology on which cloud computing is based, the service and deployment models used in cloud computing, how cloud computing works, the advantages and disadvantages of cloud computing, and the gaps in cloud computing literature.

2.1.1. Definition of Cloud Computing

The need for the formulation of a proper definition of cloud computing cannot be overemphasized (Jaatmaa, 2010). Vaquero et al (2009) assert that this will not only help to demarcate the ambits of cloud computing, it would also help to lay emphasis on the potential benefits of cloud computing adoption. Notwithstanding this, Jaatmaa (2010), Smith (2009) and Weinhardt et al (2009) are in agreement that such a definition is still lacking, and that the definitions currently available fail to properly distinguish cloud computing from other associated technologies like grid computing. Consequently, this section begins by reviewing the various definitions of cloud computing extant in cloud computing literature, before offering a standard definition.

Even though “cloud computing” is a relatively new terminology in computing discourse (Shimba, 2010; Buyya et al., 2008); the cloud computing concept has already been viewed as a model which heralds the onset of a new paradigm in the computing world (Shimba, 2010; Luis et al., 2008). In an attempt to un-package the concept, many definitions of cloud computing have been offered.

McDonald, McDonald, and Breslin (2009, p.5) define cloud computing as the “delivery of elastic computing resources over the internet by external service providers.” In ascribing elasticity to the concept, they acknowledge the scalability and massive storage and cloud capabilities that come with this new paradigm, and hint at the outsourcing element or service provision shift to external vendors that is inherent in the paradigm. Catteddu and Hogben (2009), Plummer et al (2009), and Jeffrey & Neidecker-Lutz (2009) also allude to the scalability and outsourcing elements of the cloud computing concept in their definitions.

Mell & Grance (2009, p. 1) and Padmanabhan (2011) adopt the formal definition which has been advanced by the National Institute of Standards and Technology (NIST), which views cloud computing as “a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” Beyond pointing at the outsourcing, scalability, shared nature, and means of transmission of services of cloud computing; this definition also anticipates a series of potential benefits attributable to cloud computing. These include convenience, on-demand availability, and minimal upfront investment in IT infrastructure by the clients.

Other definitions have focused less on the potential benefits or inherent characteristics of cloud computing, and more on the (technical) means by which its services are delivered. For example, quoting the European Network and Information Security Agency (ENISA), Cattedu and Hogben (2009) define cloud computing as the “on-demand service model for IT provision, often based on virtualization and distributed computing technologies.”

Buyya et al (2008, p.3) also adopt a similar approach, but extend their definition to clarify the nature of the contractual relationship between the service providers and their clients/users. They define cloud computing as “a type of parallel and distributed system consisting of collection of interconnected and virtualized computers that are dynamically provisioned and present as on or more unified computing resource based on service-level agreements established through negotiation between service provider and customer.” Like Buyya et al (2008), Luis et al (2009, p.51) also clarify the contractual nature of the relationship between service providers and clients in the cloud computing environment, when they embed the type of contract (personalized service level agreements) as well as the nature of the financial obligation (pay-per-use) in the definition. Their definition views cloud computing as:

…a large pool of easily usable and accessible virtualized resources (which) can be dynamically reconfigured to adjust a variable load (scale), allowing also for an optimum resource utilization. This pool of resources is typically exploited by a pay-per-use model in which guarantees are offered by the infrastructure provider by means of customized SLAs.

Synthesizing the various definitions given above, cloud computing can therefore be defined as a network-enabled model offered by a service provider and relying on distributed computing technologies to provide easy, pervasive, and convenient access to virtualized resources by multiple clients. These virtualized resources may include hardware, services, or platforms. The resources offered are scalable, and provide an array of potential benefits to the clients, including but not limited to: convenience, on- demand availability, and minimal upfront investment in IT infrastructure by the clients.

The service providers and clients enter into personalized service level agreements (SLAs), where the service providers typically guarantee the quality of service in return for a monetary consideration which is discharged via a pay as you go model.

The definition of the cloud computing concept provides the basis for the identification of cloud computing characteristics, which are discussed in the next subsection.

2.1.2. Characteristics of Cloud Computing

In evaluating the characteristics of cloud computing, the majority of research studies have adopted the bi-dimensional dichotomy first used by NIST, which bundles such characteristics into two broad groups: “essential characteristics and common characteristics” (Shimba, 2010, p.13; Plummer et al, 2009; Grance, 2010). Accordingly, research studies have been unanimous in identifying and attributing thirteen characteristics to cloud computing, eight of which are regarded as being common and the remaining five as being essential (Shimba, 2010). Essential Characteristics of Cloud Computing

One of the major essential characteristics identified by NIST, and which also follows from the definitions of Cattedu & Hogben (2009), Mell & Grance (2009, p. 1) and Padmanabhan (2011) as outlined above is that of “on-demand self-service” (Shimba, 2010). This implies that the cloud computing offers users the capability of accessing services whenever or wherever they need such services and that such access is done with minimal or no interaction between the user and the service provider.

The second essential characteristic identified by NIST is that of “broad network access.” This means that the users are able to access the resources offered by cloud computing only over interconnected networks (the internet), that such access is achieved through conventional mechanisms, and that such access is personalized.

An inherent characteristic of cloud computing, as explicated in most of the definitions presented in the preceding section is that of scalability. Accordingly, NIST and Shimba (2010, p.14) identify “rapid elasticity” as another essential characteristic of cloud computing. This implies that resource capability is theoretically unlimited and can either be scaled up or scaled down to meet the firm’s changing resource needs, as and when such changes occur.

The other essential characteristic of cloud computing as identified by Shimba (2010) is that it is measurable. This measurability therefore facilitates control and monitoring, and enhances transparency between service providers and their clients/users. The final essential characteristic attributed to cloud computing is that of “resource polling.” This means that cloud computing enables the dynamic and mutual sharing of disparate virtual and physical vendor resources, with the ultimate goal of serving multiple clients or users (Shimba, 2010). Common Characteristics of Cloud Computing

As mentioned, a number of other common characteristics relating to cloud computing have been outlined, apart from the five essential characteristics presented above (Shimba, 2010; Vouk, 2008). These are also discernible from the various definitions presented, and include the use of a pay as you go model, which means that the clients only pay for what they have used and only when they use it. Others include: minimal upfront IT and personnel investment costs, the deployment of virtualization technology, minimal IT and personnel running costs, geographical dispersion of the clouds, as well as “massive scale availability of computing and storage capabilities, homogeneity, (and) resilient computing” (Shimba, 2010, p.14).

2.1.3. Cloud Computing Technology

Gaining a proper understanding of the meaning and characteristics of cloud computing is a necessary but by no means sufficient condition for interrogating the factors which affect the adoption of cloud computing (Jlelaty & Monzer, 2012; Marston et al, 2011). Consequently, it is also necessary to understand the technology on which cloud computing is underpinned (Jlelaty & Monzer, 2012; Marston et al, 2011).

Accordingly, Shimba (2010), Wang and Laszewski (2008), Luis et al (2008) and Jlelaty & Monzer (2012) assert that cloud computing is the outcome of multiple rather than a single technology, and go ahead to identify various core technologies as well as business models on which the concept of cloud computing is anchored. According to Jlelaty & Monzer (2012, p.11) these include “virtualization, multi-tenancy, and web services.” On his part, Shimba (2010, p.9) identifies the following core technologies as forming the basis of cloud computing: “grid computing, virtualization, parallel computing, service oriented architecture (SOA), the Internet, autonomic system computing, Web services, web application frameworks and open source software.”

Virtualization refers to the formation of a virtual copy of something. Typical resources which are virtualized include operating systems, storage devices, servers, and network resources. As it applies to operating systems, virtualization can be defined as the process of deploying software in order to facilitate the simultaneous execution of several operating systems on a given hardware. With respect to networks, virtualization involves the fragmentation or division of the existing bandwidth into channels, each of which is autonomous, and can be allotted to a specific server or hardware device in real time. This division or fragmentation results into a combination of the existing resources. The end result is that network intricacy is concealed since it is unscrambled into manageable fragments. As applied to storage devices, virtualization refers to the process of aggregating all the storage capacity from all the storage devices in the network into a superficial single storage device. This single storage device is then run from a central control point. When applied to servers, virtualization means concealing the resources of the server from the users. This frees the user from the need to understand or even administer complex server details or resources, enhances resource sharing and consumption, and provides significant scope for future expansion or scalability.

Multi-tenancy is also a principle technology underpinning cloud computing. It refers to the use of a single software instance or hardware system to serve more than one client or users, as opposed to single-tenancy where a software instance is run for every customer on the network. Thus, in a multi-tenancy architecture, many users share the system resources and applications.

Web services involve the deployment of open standards such as XML over internet protocol backbones, with an aim of assimilating internet-based applications in order to facilitate communication between different machines within a network without the need to engage in time-wasting coding operations.

Grid computing is a type of distributed computing system, where the distributed computing system refers to a formation composed of several autonomous computers communicating with each other via a network. However, grid computing can be contrasted from the conventional network by the fact that grid computing does not focus on inter-device communication but taps into the idle processing cycles of the machines in the network in order to decipher problems which are too intricate to be solved by a freestanding machine.

Parallel computing involves the deployment of computer systems in order to solve problems. Unlike its serial computing, its predecessor, parallel computing is grounded on the assumption that large problems can be broken down into smaller ones, which can then be resolved simultaneously on different CPUs. Serial computing, in contrast, involved decomposing problems into instructions which were then solved sequentially on a single CPU.

Service oriented architecture refers to a software configuration which enables the aggregation of services that are interoperable or can communicate with each other. Autonomic computing is based on advanced artificial intelligence, and is designed to mimic the human autonomic nervous system. It describes distributed computer systems which are “self-healing, self-configured, self-protected and self-managed” and whose operations are concealed or hidden from users (Laster & Olatunji, 2007, pp.62-63).

Web application frameworks describe software structures which are designed to facilitate the development of dynamic internet-based services, applications, and websites.

Examples of web application frameworks include: Joomla, Wordpress, Symphony, and CakePHP.

Open-source software refers to computer programs which are characterized by various features, including: free redistribution, they are available with the source code; they come with open-source licenses which allow users to modify or study the software, and are developed collaboratively and in public. Finally, the internet refers to the global network of networks. It brings together all the computer networks in the world, which are connected together by means of standard protocols (typically the TCP/IP).

In summary, cloud computing is based on a number of technologies, including: “grid computing, virtualization, parallel computing, service oriented architecture (SOA), the Internet, autonomic system computing, Web services, web application frameworks and open source software.” Having described each of these, we now turn our focus on service models in the next subsection.

2.1.4. Service Models

Most research studies identify three forms of cloud computing service models, including: SaaS (or Software-as-a-Service), PaaS (or Platform-as-a-Service), and IaaS (or Software- as-a-Service) (Shimba, 2010; Jlelaty & Monzer, 2012; Ahronovitz et al, 2010; Mell & Grance, 2009).

In the SaaS model, the firm or entity in need of services outsources their provision to external vendors. The services are accessed by the user remotely through the internet. The user is only allowed to use the applications on offer, but is not given control of the software, or allowed to access its design, or the hardware / network platform on which it runs (Jlelaty & Monzer, 2012; Shimba, 2010; Mell and Grance, 2009). In the PaaS model, the users rent dedicated resources from the service provider. They are allowed to host applications or software which they themselves have created, using the service provider’s platforms. As such, the users have control over the applications, but they have no control over the cloud infrastructure (Shimba, 2010). Under the IaaS model, users are offered dedicated resources for their own exclusive use, and are not allowed to share such resources with other third parties. The user may install applications such as operating systems on the cloud infrastructure. The user is also allowed control over storage, applications, operating systems, or network modules, but is not allowed any control over the cloud infrastructure (Mell & Grance, 2009; Shimba, 2010).

2.1.5. Deployment Models

These refer to how the cloud computing services are disseminated to the users or clients. Four types of cloud computing deployment models have broadly been outlined in literature. These include: the public cloud, private cloud, community cloud, and the hybrid cloud (Shimba, 2010; Jlelaty & Monzer, 2012; Ahronovitz et al, 2010; Amrhein et al, 2010; Mell & Grance, 2009).

In the public cloud, the services are offered to the users via the internet. These services are often low-priced and may even be free in certain cases. Even though the services are offered over the internet, the user or client data is often hidden or invisible to other users, and the users are provided with control touch points through which they are able to control who accesses their data, when, and how (Jlelaty & Monzer, 2012). The services offered are paid for using the pay-as-you-go-model, contractual obligations are enforceable by means of service level agreements (or SLAs), clients are able to set the security level which they are comfortable with, and the management of the shared infrastructure is the responsibility of the service provider (Shimba, 2010).

Unlike in the public cloud, in the private cloud resources are not shared. The resources will either be situated in-house or offsite, access to the resources by the public is impossible (since access is both designated and restricted), and the user does not use the public cloud. While the private cloud frees the user from security and compliance issues, it requires massive capital costs (Shimba, 2010). The private cloud has fewer bandwidth restrictions than the public cloud, allowing the users or clients greater control over their data and operations. It also offers clients more control over the infrastructure, which goes a long way towards enhancing security (Jlelaty & Monzer, 2012).

The hybrid cloud brings together characteristics of various cloud deployments, such as the private and public clouds. Each of the clouds under the hybrid system retains its distinct identity, and the various clouds under the hybrid system are held together by means of exclusive or common technology. For example, in a hybrid deployment bringing together private and public clouds, the client would be able to use both of the clouds but the public would still have no access to the cloud (Shimba, 2010). In such a hybrid formation, the client may decide to have non-critical data manipulated via the public cloud while-critical data would be handled in the private cloud server (Jlelaty & Monzer, 2012).

The other deployment model is the community cloud. Here, the cloud infrastructure is both owned by a group of organizations/clients who possess like or common interests. They may or may not run the infrastructure, the infrastructure may be located onsite or offsite, but they have shared access to the cloud resources. The public may also have access to the resources in this cloud, in some cases (Shimba, 2010; Jlelaty & Monzer, 2012).

2.1.6. How Cloud Computing Works

The cloud computing system can be represented by means of a diagram as shown in Figure 1 below:

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Figure 1. How Cloud Computing Works

As figure 1 above illustrates, the entire system can be viewed as consisting of two broad parts: the front end and the back end. The front end is the client/user end, while the back end is the cloud computing system put together by the service provider. These two ends are connected together by means of a network, which typically is the internet.

The user’s end (the front end) will comprise of the user’s computer, together with the applications by which the user accesses the cloud computing system. The back end on its part comprises of various components, including servers, storage devices, and the computers which collectively make up the cloud system. It also includes the operating and application software used to run the system. Every one of these applications being run on the back end has a server dedicated specifically for it.

The entire cloud computing system is run by a central server, which tracks the traffic getting into and out of the system, as well as the demands of the clients, and sees to it that everything is executed flawlessly. The central server operates in accordance with a set of protocols, and utilizes middleware - a type of software which facilitates communication between networked computers.

In many instances, the servers do not run full throttle, resulting in some of the processing power lying idle. Through server virtualization, the idle processing power can be tapped and the capacity of the servers optimized, reducing the need to acquire more physical machines. The service providers make copies of all the data belonging to the clients which is stored in the cloud computing system, and backs it on other storage devices so that in case there is a breakdown in any of the cloud computing devices the data can be safe.

2.1.7. Cloud Computing Applications

Cloud computing has been deployed in many applications. One of the applications where cloud computing has been extensively used is in the social media, where social networking sites, article directories, and video and image sharing sites such as YouTube, Flickr, and Slide share store user data such as photographs, videos, and PowerPoint slides in the cloud so that the users don’t have to invest in physical storage devices to store them for themselves.

But the applications have by no means been restricted to social media applications. Cloud computing applications have also been created to perform a wide array of computing tasks, including: e-mail, time-management, discussion groups, word processing, data storage, presentation, wikis, web creation, file hosting, project management, customer relationship management, contact management, online chat, note taking, accounting, and payroll management applications, among many others.

Examples of each of these cloud computing applications, as discussed above, can are given in Table 1 below:

Table 1. Applications of Cloud Computing

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2.1.8. Advantages of Cloud Computing

Cloud computing has been associated with a number of advantages. According to Shimba (2010), cloud computing facilitates the pooling of resources, which results into the achievement of scale economies that ultimately translate into low upfront investment costs in IT infrastructure as well as low overhead and maintenance costs. As Marston et al (2011) demonstrate, such cost economies have the potential to increase cost savings for the firms, and lead to a reduction in total costs of between five to seven times. Additionally, since cloud computing facilitates the deployment of parallel and scalable computing, it has been associated with higher performance levels. It eliminates the need to maintain some of the computing hardware in-house, facilitates collaboration and universal access to resources, and eases the ability to take certain specific security procedures (Shimba, 2010; Voona and Venkantaratna, 2009, Buyya et al., 2008).

According to Jlelalty & Monzer (2012), the scalability of cloud computing offers a major point of strength for the technology. The scalability enables firms to either upgrade or downgrade their resource requirements, which endows such firms with a high degree of “strategic flexibility” (Jlelalty and Monzer, 2012, p.16; Marston et al., 2011).

Several research studies have evaluated the importance of cloud computing from an environmental point of view. For example, Marston et al (2011) demonstrate that in shifting their IT functions and resources to the cloud, organizations are able to cut back on their IT infrastructure as well as on their energy consumption, thus giving true meaning to the concept of “green IT.” This point has however been contested by other researchers such as Kim et al (2009) who contend that moving to the cloud instead increases the power consumption of the cloud servers, which ends up cancelling out any efficiency gains and that cloud computing therefore does not necessarily lead to the reduction of global carbon emissions.

Yet another aspect of cloud computing which has been proposed to offer major advantages is the cost element. According to Jlelalty & Monzer (2012) and Benlian & Hess (2011), cost advantages accruable from the adoption of cloud computing, and especially SaaS, are significant. As Marston et al (2011) aver, firms which do not deploy cloud computing technology end up committing huge portions of their resources to setting up IT infrastructure, notwithstanding the fact that the servers will have to be changed within every three years and the maintenance and administrative costs of the systems, which end up substantially inflating IT costs within the organization. As such, the adoption of cloud computing can eliminate these costs and present the firms with huge savings.

Cloud computing also has an impact on industry structures, and in the process has beneficial outcomes for small businesses. The huge IT investments required for successful competitive positioning in certain industries act as formidable entry barriers to small businesses, especially those in the developing countries. Since cloud computing voids the need to invest in such infrastructure, it eliminates this entry barrier for such businesses and therefore facilitates easy or free entry into such industries (Marston et al, 2011; Jlelalty & Monzer, 2012). According to Jlelaty & Monzer (2012), cloud computing facilitates the outsourcing of many non-core computing functions to service providers and therefore helps in eliminating some of the overhead costs that come with the extra personnel required to be engaged if the outsourced solutions were to be performed in- house.

However, a number of studies have also contended that the perceived cost advantages of cloud computing has been overrated, and that in actual fact such advantages cease to exist when hidden costs are taken into account. Accordingly, a number of researchers have attempted to factor the hidden costs of cloud computing into account. For example, in evaluating the costs of adopting cloud computing systems, Kim et al (2009) demonstrate that even after paying for the cloud computing service using the pay-as-you-go model, users cannot fully rely on the service providers to provide maintenance and administration services for the cloud computing systems and have to do that on their own, which translates into added costs and more time. All in all however, most of the researchers have balanced the potential economic costs of adopting cloud computing solutions against the potential cost savings an conclude that cloud computing offers significant potential to achieve huge cost savings if the economic risks associated with this technology are well handled (Shimba, 2010).

Additionally, given its credentials as an “innovative disruptive technology”, cloud computing comes with the promise and potential of facilitating richer functionality in applications. Additionally, given that it results into the outsourcing of daily mundane and repetitive tasks such as system administration and maintenance to third party providers, it comes with the added advantage of freeing the IT personnel in the organization to focus on more value-adding and innovative activities (Marston et al., 2011).

Apart from the advantages or benefits already outlined, a number of studies have found positive correlations between the adoption of cloud computing systems and to-market speeds. For example, Jlelaty & Monzer (2012) assert that the adoption of cloud computing systems by organizations has the potential to reduce the firm’s to-market speeds from months to just a few weeks or days. This is because the adoption of cloud computing helps the organization to reduce the time required to procure software and hardware for its operations, to raise the capital outlay which would otherwise be required to implement the computing system in-house if the system were not outsourced to service providers, and the time to purchase the necessary hardware and software requirements. Additionally, the cloud computing system has the potential to enable organizations to launch their products or services into the market faster compared to other players (Jlelaty & Monzer, 2012).

Another advantage of cloud computing systems over traditional grid systems is that they have been associated with higher levels of user-friendliness. This is because in outsourcing their resource requirements, users are freed from the need to perform a variety of tasks by the service providers, and running of the front end system becomes highly simplified for them (Jlelaty & Monzer, 2012).

2.1.9. Disadvantages of Cloud Computing

Cloud computing has also been associated with a number of potential disadvantages. For example, while cloud computing has been associated with the potential of significant cost savings, a number of research studies have associated the adoption of the technology with hidden costs which can lead to a negative impact on the bottom-line if the potential economic risks are not well addressed (Kim et al, 2009; Shimba, 2010).

Miller (2008), Shimba (2010), and Jeffrey & Neidecker-Lutz (2009) have also associated cloud computing with several other disadvantages, including: the possibility of persistent downtimes, slow internet speeds, exposure to the risk of loss of data, security risks, and restricted service or product features from vendors.

Shimba (2010) has dwelt at length on the issue of security in cloud computing adoption. He asserts that the multi-tenancy environment of cloud computing greatly enhances the security challenges which organizations or individuals using cloud computing systems are exposed to. Additionally, cloud computing necessarily transfers the ownership of control from the user to the service provider, and this has the potential to impact negatively on the user’s data integrity or on the integrity of the user’s applications. This is especially the case when, as happens very often, service providers include explicit disclaimers in their service level agreements on their responsibility towards security threats such as “unauthorized access, use, corruption, (and) deletion” of the client data hosted in the cloud (Shimba, 2010, p.36).

Additionally, the cloud computing systems have been associated with the “lack of procedures and standards for data format or service interfaces that could guarantee portability and interoperability between applications and services and between vendors”, which forces clients to be locked in to particular services providers. This has the effect of increasing the bargaining power of the service provider to the detriment of the user’s welfare (Shimba, 2010). Such locking in may also lead to inflexibility on the part of the user since some applications provided by the service providers are proprietary and documents created using such applications cannot be used with other applications.

Shimba (2010) also asserts that cloud computing is more prone to “guest-hopping attacks” compared to grid computing systems. Not only that, the cloud computing environment provides fertile grounds for malicious insider attacks. Since the cloud computing architecture is configured after the distribution fashion, it is also more vulnerable to attacks such as “replay attacks, man-in-the-middle attacks, sniffing and spoofing” (Shimba, 2010, p.37). Moreover, cloud computing systems face increased security risks arising from the violation of interface integrity. For example, based on the vulnerabilities typically associated with web browsers, Jensen and Schwenk (2009) show that, the possibility of manipulating browsing services in cloud computing systems is high. Other security risks which have been associated with cloud computing systems include DDoS (distributed denial of service attacks) and data leakages, among many others (Shimba, 2010; Jensen & Schwenk, 2009).

Since organizations or individuals who have adopted cloud computing are reliant on the internet, they are exposed to the possibility of disruptive downtimes since when the internet connection times out, which often occurs even with highly reliable service providers.

2.1.10. Gaps in Cloud Computing Literature

Even though cloud computing is one of the hottest growth areas in the field of IT today, the existing body of literature related to cloud computing remains surprisingly small (Jaatmaa, 2010; Sriram & Khajeh-Hosseini). Using “cloud computing” as the key phrase, Jaatmaa (2010) carries out an extensive search of peer-reviewed articles on respected databases such as Scopus and finds only 250 scholarly articles on the subject, with the earliest such paper dating back to the year 2007. Contrasting this find with article finds in other IT-related disciplines such as “web 2.0”, Jaatmaa (2010) finds more than 1,100 scholarly articles for the latter. In some developed countries such as Finland, where the diffusion of such technology is expected to be very high, Jaatma (2010) finds only two peer-reviewed studies, which include those of Kettunen (2009) and Ristola (2010).

Breaking down the articles into various categories on the basis of subject area (for example, computer science, social sciences, business, engineering, and material science), Jaatmaa (2010) finds that the number of studies is not only few but that it is also spread too thinly as is illustrated by Figure 2 below:

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Figure 2. Number of technology adoption studies: (Jaatmaa, 2010, p7)

Acknowledging the lack of a prior systematic effort to review the agenda of the peerreviewed articles on cloud computing undertaken thus far, the study by Sriram & KhajehHosseini (2010) represents the first such attempt to undertake a systematic review of cloud computing studies.

Using a string of search-relevant keywords, Sriram & Khajeh-Hosseini (2010, p.1) undertake an extensive search on various databases and search engines, including “ACM Digital Library, IEEE Xplore, Springer Link, Science Direct and Google Scholar.” They find only 150 papers, buttressing the position of Jaatmaa (2010) regarding the paucity of such studies.

While Jaatmaa (2010) categorized the studies on the basis of disciplinary focus, Sriram & Khajeh-Hosseini (2010) categorize the studies on the basis of the subject focus of the papers. Accordingly, they identify seven key areas which cloud computing studies have focused on. These areas, and the studies undertaken, are summarized in the table below:

Table 2. Key Focus Areas for Cloud Computing Studies

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Source: Sriram & Khajeh-Hosseini (2010, p.2)

Evaluating the seven categories, Sriram & Khajeh-Hosseini (2010) conclude that cloud computing literature has focused on two broad areas: cloud computing studies have generally revolved around the technical implications of implementing cloud computing solutions, and on the impact of cloud computing adoption by individual and organizational users. Consequently, the behavioral aspects of cloud computing adoption, and especially using adoption models as a theoretical basis, remain least studied and understood, a gap which this study seeks to fill.

2.2. Empirical Research in Relevant Disciplines: Theories of Technology Adoption

2.2.1. Theory of Reasoned Action

The theory of reasoned action (TRA) has been attributed to Fishbein & Ajzen (1980). The TRA asserts that an individual’s behavioral intention is the strongest predictor of that individual’s behavior. The individual’s behavioral intention is itself a function of two factors: the individual’s attitudes and his subjective norms. The subjective norms refer to the influence of significant others on the individual’s behavior, while attitudes refer to an individual’s predisposition to act in a certain way and are shaped by values and beliefs. Collectively, these influence the individual’s behavior, and this can be depicted in the form of a diagram, as shown in Figure 3 below:

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Figure 3. Theory of Reasoned Action: Source: Ajzen & Fishbein, 1980 p.8


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Technology Trade Theory (TripleT)
Girne American Universtity  (College of Business)
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Triple T model, Cloud Computing, Information Technology Executives, TAM model, Technology Acceptance Model, Social Exchange Theory
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Mohammad AbdulQadir Obeidat (Author), 2013, Technology Trade Theory (TripleT), Munich, GRIN Verlag,


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