A modified Brown and Gibson model for cloud service selection.

Cloud computing has been widely accepted in the information technology (IT) industry as it provides on-demand services, lower operational and investment costs, scalability, and many more. Nowadays, small and medium enterprises (SMEs) use the cloud infrastructure for building their applications, which makes their business more agile by using elastic and flexible cloud services. Many cloud service providers (CSPs) have offered numerous services to their customers. However, due to the vast availability of cloud services and the wide range of CSPs, decision-making for cloud selection or adopting cloud services is not consistently straightforward. This paper proposes a modified Brown and Gibson model (M-BGM) to select the best CSP. We consider both the subjective and objective criteria for the non-quantifiable and quantifiable values, respectively. Here, various decision-makers can express their views about the alternatives. We compare M-BGM with multi-attribute group decision-making (MAGDM) approach and perform a sensitivity analysis to show the robustness.