Developing a Cloud-Computing Adoption Framework

Technological Context

The technological context comprises the variables that influence an individual, an organization and an industry’s adoption of innovations (Claycomb et al., 2005; Huang et al., 2008). It includes five innovation attributes (from IDT) that influence the likelihood of adoption (Dedrick and West, 2003; Rogers, 1983). Researchers have also included several other variables such as system assimilation, compatibility, trailability, observability, complexity, perceived direct benefits, relative advantage, perceived indirect benefits and standardization (Hossain and Quaddus, 2011; Huang et al., 2008; Jang, 2010; Musawa and Wahab, 2012; Raymond and Uwizeyemungu, 2007; Thiesse et al., 2011).

Organizational Context

It refers to descriptive measures related to organizations such as firm scope, firm size and managerial beliefs, etc. (Salwani et al., 2009). Adoption propensity is influenced by formal and informal intra-organizational mechanisms for communication and control; along with resources of firms (Dedrick and West, 2003). Variables in organizational context include financial resources, firm structure, organizational slack, innovation capacity, knowledge capability, operational capability, strategic use of technology, trust, technological resources, top management support, support for innovation, quality of human capital, organizational knowledge accumulation, expertise and infrastructure and organizational readiness, financial capacity and technology competence (Carnaghan and Klassen, 2007; Gupta and Shukla, 2002; Lee et al., 2010; Lin, 2009; Musaw and Wahab, 2012). Similarly, role of top management commitment, potential power of the partner, trust in the partner and relationship commitment with a partner are also important (Li et al., 2010).

Environmental Context

It focuses on areas in which a firm conducts its business operations, with the priority given to external factors influencing the industry such as government incentives and regulations (Salwani et al., 2009). It includes variables related to industry characteristics such as rivalry, relations with buyers and suppliers, as well as the stages of the industry life cycle (DePietro et al., 1990, pp. 151–175).

Limitations of TOE Framework

Studies based on the TOE framework have several limitations too. According to Dedrick and West (2003), TOE framework is just a taxonomy for categorizing variables and it does not represent an integrated conceptual framework or a well developed theory, hence, there is a requirement of a more robust framework to study organizational adoption. Low et al. (2011) also highlighted that TOE framework has no major constructs in the model and the variables in each context. TOE framework is limited in its explanatory power of technology adoption (Musawa and Wahab, 2012).

Developing Extended TAM–TOE Framework

This study takes into consideration two of the technology adoption models, that is, the TAM model and the TOE framework which have been widely adopted for studies in an organizational context. Considering their individual limitations, researchers have advocated the need of integrating TAM and TOE so that predictive power of the resulting model can be improved and some of their individual limitations can be overcome.

Integrating the two models (TAM and TOE) is not simple because the external variables of the TAM model and the variables of the TOE framework vary across contexts and their significance as well. Thus, there is a lack of a common set of variables which can be generalized to explain technology adoption and is applicable to any context and technology. To develop an integrated model, this study follows an approach of including all the variables (significant as well as insignificant) of TAM and TOE identified from various studies based on these two models. Further, specific variables to cloud computing, that is, security and third-party control are identified from the literature that describe its technical dimension and they are considered as separate set of variables while integrating the model. These variables are included so that integrated model can be more robust and relevant for cloud computing adoption.

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Figure 1.

Source: Devis et al. (1986); Tornatzky and Fleischer (1990).

The next issue that arises is related to the approach of integration. This study proposes to consider technological and organizational variables of the TOE framework as external variables of the TAM model while environmental variables of the TOE framework are proposed to have a direct impact on adoption. In the proposed model, cloud computing-specific variables are treated as external variables of TAM. The pictorial view of the proposed model is presented in Figure 1. This approach is based on the foundation that ‘integrating different models, each making up another, has emerged as a new trend in IS related research’ and has proved useful while considering the limitations of various innovation adoption theories and models (Hongjun and Xu, 2010).

Relative Advantage

Relative advantage means that ‘the degree to which a technological factor is perceived as providing greater benefit for firms’ (Rogers, 1983). Cloud computing has an advantage over other technologies such as reduced cost, scalability, flexibility, mobility and shared resources (Zhang et al., 2010). Using cloud computing, managers can use shared resources (Marston et al., 2011) and rented services on pay-as-you-use basis which lead to adjusting the level of usage according to the current needs of the organization (Feuerlicht and Govardhan, 2010, pp. 1–8) and frees them from administering and maintaining IT infrastructure every year. As the requirements of cloud computing increases, the cloud user should be able to scale up their resources and infrastructure to satisfy the adaptors’ new requirements of storage, number of servers, processing and connection bandwidth (Benlian and Hess, 2011; Kim et al., 2009). Mobility offers users the facility of accessing and working on their documents from anywhere in the world; provided they have a computer access and an Internet connection (Jain and Bhardwaj, 2010). Users need not own a computer for using services of cloud computing.

Compatibility

Rogers (1983, p. 240) defined compatibility as ‘the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters’. Studies in IT adoption have witnessed valid role of compatibility in technology adoption, as well as in perceived usefulness (Calisir et al., 2009; Chen and Tan, 2004; Peng et al., 2012). It is perceived that more the cloud computing platforms are in align with the Internet platform, the organization will be able to develop more capacity to utilize the benefits of cloud computing and more is the possibility of reducing the degree of uncertainty among the users of technology. In the case of cloud computing, it is needed to take into account the integration (convenience of application import and export) and customization (adjustment of services). Géczy et al. (2012) have also explained that cloud-based services should be compatible with the existing formats, interfaces and other structured data, or else integration and customization services should be provided by the cloud service providers.

Complexity

Complexity is defined as the perceived degree of difficulty of understanding and using a system (Sonnenwald et al., 2001). In terms of IT adoption, it is measured as time taken to perform tasks, integration of computer results into existing work, efficiency of data transfer, system functionality and interface design, etc. Based on these studies, it can be inferred that complexity is inversely proportional to ease of use, usefulness and adoption intentions (Chau and Hu, 2001; Igbaria et al., 1995; Parveen and Sulaiman, 2008).

Organizational Readiness

Tan et al. (2007) described organizational readiness as ‘managers’ perception and evaluation of the degree to which they believe that their organization has the awareness, resources, commitment, and governance’ to adopt an IT. Broadly, it has been described with two dimensions, that is, financial readiness (financial resources for cloud computing implementation and for ongoing expenses during usage) and technological readiness (infrastructure and human resources for cloud computing usage and management, Musawa and Wahab, 2012; Oliveira and Martins, 2010). We argue that firms that have effective infrastructure, expertise in their employees and financial support are more likely to adopt cloud computing.

Top Management Support

The IT adoption literature has recognized the role of top management support in initiation, implementation and adoption of several information technologies (R.K. Singh, 2013). Salwani et al. (2009) explains it as the perceptions and actions of top officials on the usefulness of technological innovation in creating values for the firm. It ensures long-term vision, reinforcement of values, commitment of resources, optimal management of resources, cultivation of favourable organizational climate, higher assessments of individual self-efficacy, support in overcoming barriers and resistance to change (Das, 2003; Jang, 2010; Malhotra, 2010; Ramdani et al., 2009; Teo et al., 2009; Wang et al., 2010). Also, top management support positively affects perceived usefulness and perceived ease of use (Davis, 1989).

Training and Education

Training is described as a degree to which a company instructs its employees in using a tool in terms of quality and quantity (Malhotra, 2010; Pillania, 2006). Since cloud computing is a complex information system, an organization needs to train and educate its employees before implementing it. It reduces employees’ anxiety and stress about the use of cloud computing, and provides motivation and better understanding about its benefits for their tasks. It reduces ambiguity and help employees developing knowledge for effective usage in future. It also improves its perceived ease of use and usefulness.

Competitive Pressure

From the early stages of research in technology adoption, the role of competitive pressure is recognized as an effective motivator (Dasgupta and Gupta, 2009; Lin and Lin, 2008; Lippert and Govindarajulu, 2006). Zhu and Kraemer (2005) defined it as ‘the degree of pressure that the company feels from competitors within the industry’. Competition in the industry is generally perceived to positively influence the IT adoption specially when technology directly affects the competition and it is a strategic necessity to adopt new technologies to compete in the market (Ramdani et al., 2009). This fact is applicable in the context of cloud computing. Adopting information systems is useful for a firm to alter the competitive environment in terms of rules of competition, industry structure and outperforming their competitors (Porter and Millar, 1985).

Trading Partner Pressure

Trading partner pressure can be described as pressure from trading partners to implement and adopt a technology. Many studies have advocated its significant and positive contribution in the degree of intention to adopt and use information technologies (Lin and Lin, 2008; Lippert and Govindarajulu, 2006; Teo et al., 2009; Wang et al., 2010). Support from trading and business partners ensure its effective implementation, market acceptance and value maximization (Teo et al., 2009). A firm’s decision to adopt cloud computing may be influenced by adoption status of its trading partner along the value chain. Keeping in mind the complex architecture of cloud computing, its adoption may require tighter integration of customers, business partners and suppliers.

Security

Security is seen as data confidentiality, auditability, loss of data, data storage security, data transmission security and breach of privacy in the business operations (Armbrust et al., 2010; Bhasin, 2006; Bristow et al., 2010; Gupta and Sareen, 2001). Security concerns are high in the case of cloud computing because the data placed are easy to locate, to send across communication channels of different countries, where data privacy laws are potentially different and therefore there are chances of potentially sensitive data getting exposed to snooping eyes of unauthorized individuals (Tout et al., 2009). Based on the literature review on cloud computing, security can be expressed in terms of:

Threats—A threat is what we are trying to protect against. According to Chow et al. (2009), cloud service providers encounter these threats by matured and tested security measures and processes as well as by preferring to enforce security via contracts with online services providers over via internal controls. Certain other threats include the loss of physical control of the data, lack of standards, security, regulation at the local, national and international level and insufficient uptime for mission-critical applications for large organizations.

Third Party Control

It is another major concern in cloud computing adoption related to the cloud provider; responsible for managing the cloud services. These cloud services are:

Availability—It refers to the accessibility and readiness of the services. The cloud users want the data to available all the time or rather, at the time when they need to use it. This raises the concerns over the effectiveness of cloud service providers in terms of their availability. Kim (2009) argues that adoption of high availability architecture, and tested platforms and applications provide 100 per cent availability of data. Service level agreements (SLA) and a combination of precautionary measures (backup on on-premises storage, backup cloud, etc) are the main driving factor to ensure desired levels of availability.

There are issues in understanding the complexity, control and transparency according to the regulatory compliance of legal implication of the data being held by a third party (Chow et al., 2009). To avoid such issues, companies have been building private clouds. Other issues are related to proprietary format of locking the data, and related with training and processes. Having no control over frequent changes in cloud-based services which require standardization for cloud related activities. Another concern is related to transitive nature of cloud service providers. Security issues are more prominent to deal with when cloud providers contract some of their services to subcontractors over whom cloud users have even lesser control and less trust.

Perceived Usefulness (PU)

PU is defined as the prospective user’s subjective probability that using a specific application system will increase his or her job performance within an organizational context.

Perceived Ease-of-use (PEOU)

PEOU refers to the degree to which the prospective user expects the target system to be free of effort (Davis, 1989). The TAM model suggests that perceived ease of use influences perceived usefulness, because technologies that are easy to use can be more useful (Schillewaert et al., 2005).