Previous research is dominated by quantitative studies when exploring organizational adoption of cloud computing (Alismaili et al., 2016a; Yang et al., 2015; Senarathna et al., 2018). Mohammed et al., (2018) and Hassan et al., (2017) both recommended the qualitative study. This qualitative descriptive study aims to address the gap in the literature by further exploring the factors that influence cloud computing adoption of IT leaders in the US, specifically in Virginia, Washington, DC, and Maryland.
Theoretical Foundations and/or Conceptual Framework
In terms of understanding how cloud computing may or may not be adopted in the context of new technologies, there are several theories that could be used to evaluate the adoption process. The first is the theory of planned behaviors (TPB), which was designed as a way of predicting the way an individual will choose to engage in a behavior at a specific time or place: it is a theory used to understand the behavioral intent of an individual in the context where they have self-control (Putraa, 2020). The theory has been used in several cases where the intent to change a behavior with respect to technology has been considered as it relates to how an organization can understand how to encourage people to adopt a technology (Putraa, 2020). It includes several key aspects, such as the attitudes of the individual, the behavioral intention, their subjective norms, their social norms, the perceived power over the factors that might influence the individual in this area, and their perceived behavioral control (Putraa, 2020). In this case, the theory is not as applicable to the current context because it focuses on the behavior of the individual, and the focus of this research is on organizational decision-making.
The technology acceptance model (TAM) is another theory that is used to explore how users come to accept and use a model (Taherdoost, 2018). The end point of the model is the actual system use, which refers to the end-point where people are using the technology for its intended use (Taherdoost, 2018). Before this stage, there is the behavioral intention, which is the intent that an individual has to use the technology (Taherdoost, 2018). This in turn has been developed after an attitude towards the technology has been formed, whether this be positive or negative (Taherdoost, 2018). This can be influenced by the perceived usefulness and the perceived ease-of-use of that technology (Taherdoost, 2018). In the case of cloud computing, for example, the perceived usefulness will relate to how well the organization thinks it will benefit the company to move away from physical infrastructure and towards having information and data online. There are also external variables included, which will include the age and gender of the individual and their access to that model. As will be shown in the next theme, there are often challenges to having access to cloud computing for those in developing countries as these individuals may not have access to the infrastructure needed to use it, such as a certain speed of internet connection (Taherdoost, 2018). While this theory is useful in understanding how individuals may come to use a technology, it does not relate to the organizational processes that form the basis of this research.
Another theory of interest is the Unified Theory of Acceptance and Use of Technology, or UTAUT (Venkatesh et al., 2003). As with the previous two theories, the focus here is on understanding the user intentions to use an information system and their subsequent behavior (Venkatesh et al., 2003). There are four constructs that form part of UTAUT, which are the performance expectancy, the effort expectancy, the social influence on the individual, and the facilitating conditions (Venkatesh et al., 2003). The performance activity refers to how well the technology is perceived to perform at the function that it is useful for, which in the case of cloud computing will be the storage and retrieval of data. The effort expectancy is how much effort will be needed to understand and use the technology and how much time could be saved in using it (Venkatesh et al., 2003). The social influence refers to the external characteristics of that technology, such as how popular the technology is in the social network of the individual or whether they need it to be able to communicate with others in their network (Venkatesh et al., 2003). Facilitating conditions refers to other constructs, such as how easily accessible it is or the cost (Venkatesh et al., 2003). In the case of cloud computing, this theory is less acceptable because, while organizations do operate within a certain realm, this cannot be compared with the social influence that is seen in individuals.

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