Adopting and Integrating Cloud Computing

Adopting and Integrating Cloud Computing

Tugrul Daim, Marc Britton, Ganesh Subramanian, Rubyna Brenden, Nuttavut Intarode
DOI: 10.4018/978-1-4666-0246-5.ch011
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Cloud Computing has been around in the background in some shape or form for decades now. Yet people still ask – what is cloud computing? What can it do, and why should it be considered for growing technology needs? In the past, businesses have integrated cloud computing partially to meet their technology needs due to skepticism, reliability, and cost of the concept. However, the era is approaching where this could be a feasible solution that meets technology needs and assists businesses in meeting their goals in a reliable and efficient way. Can businesses be convinced yet? (O’Donnell, 2009). In a nutshell, cloud computing has grown over the last ten years and is still growing but making waves in the industry now more than ever, but why all this hype? Perhaps because cloud computing is seen as a viable replacement of enterprise owned local IT infrastructure (Francis, 2009).
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With technology innovation in mind, we researched various aspects of cloud computing. The objective of our study is to predict the adoption rate of Cloud Computing in the future with a soft timeline using a scenario-based forecasting model. In the course of our research, we identified key barriers preventing this transition, created a roadmap to outline the basics of cloud computing, identification of key areas for technology integration, performed a barrier analysis, and plotted a business adoption model. We concluded with recommendations and predictions in the next few years which could serve as a tool that businesses could use to determine if cloud computing is the right step in meeting their technology and business needs.

In order to highlight the multi aspects of Cloud Computing and all that it has to offer in the next ten years. A graphical roadmap was designed to explain Cloud Computing and all it encompasses. (refer to Figure 1) The roadmap is a high level overview of cloud computing, we identified market drivers, services, providers and the underlying technology components, which distinguish them in this area. Following this, we conducted surveys with experts in the Industry. We concluded that there are three key barriers from the surveys that would impact businesses in the next ten years. This assisted us in analysis throughout the paper. We then derived a business adoption model in respect to the data collected from the surveys, and categorized businesses into four main categories and predicted the adoption rate according to a time line and cost. This analysis led to the trend analysis section of this paper, and highlighted major trends in the industry, barriers and the impact of these barriers on businesses. We then studied the data and plotted a scenario-base forecasting model to predict the adoption of Cloud Computing in relation to business adoption and technology Integration which is the focal point of our study.

Figure 1.

Research methodology


Within this report we set out to answer the following questions:

  • 1.

    What are the predominant market drivers of cloud computing?

  • 2.

    How is cloud computing services and providers aligned?

  • 3.

    What possible scenarios could play out in the future of cloud computing?

Within the report we used several methods to clearly answer these questions. We first researched the marked drivers, services and providers, provider components, and barriers and enablers of cloud computing through literature research, group brainstorming, and an expert survey. With our research we developed a roadmap of cloud computing to summarize the complexities in a visually meaningful way.

For expert survey, we used scoring method for giving and ranking the scores of each question (Uzoka and Ijatuyi, 2005; Robert and Sharif, 2008). This methodology is a simple method to rate or weight the preferences based on experts’ opinions. It is not a complicated method to calculate the data and get the results of the evaluation (Schoemaker, 1995). It uses the number that has high value to rate the most significant parameters and the lower number to rate the less significant ones.

Next, we analyzed our survey data to find out what experts think about the barriers, enablers, and future timeline of cloud computing with respect to large and small businesses. We found that the survey data fit nicely with our literature research we had compiled and verified our thoughts on the barriers and adoption rate of small and large businesses.

Finally, from our data we extracted four scenarios to forecast the future of cloud computing. These four scenarios show how the cloud computing market will react depending on how the current barriers are or are not overcome adequately.

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