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Prioritizing the Critical Factors of Cloud Computing Adoption Using Multi-criteria Decision-making Techniques

Mahak Sharma, Ruchita Gupta and Padmanav Acharya

Global Business Review, 2020, vol. 21, issue 1, 142-161

Abstract: Cloud Computing (CC) is a paradigm shift with the potential of transforming the information and communication technology (ICT) industry. ICT is an integral part of all businesses, and CC helps in lightening the burden of massive ICT investments. Thus, it is essential to understand the factors that influence CC adoption. The purpose of this study is to identify and rank critical factors for CC adoption in the Indian context. The research has adopted mixed methodology (qualitative and quantitative). Experts from 13 organizations (including 8 cloud service providers (CSPs) and 5 cloud service users (CSUs)) are interviewed. Content analysis is used to confirm existing factors and identify new factors in the Indian context. Qualitative analysis has identified four new factors, namely, ‘time to market’, ‘futuristic’, ‘resistance to change’ and ‘financial losses’ (arising from security and resource availability). The quantitative part of the research used analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (FAHP) techniques to rank the factors. The analysis revealed ‘IT service cost’ and ‘time to market’ as the most critical factor through FAHP and AHP respectively. However, ‘organization size’ is reported the least critical for CC adoption through both the methods. The results also highlight divergence among the criticality of CC adoption factors using the two techniques. The study is very useful for CSPs and key decision-makers to understand the critical adoption factors and judiciously strategize for CC service promotions. It will also help users to wisely decide while making CC adoption decision.

Keywords: Cloud computing; analytic hierarchy process (AHP); fuzzy analytic hierarchy process (FAHP); information and communication technology (ICT); India; cloud service providers (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1177/0972150917741187

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