A Novel Bhattacharya and Cosine Operator Based Enhanced Trapezoidal Bipolar Fuzzy AHP with TOPSIS for selecting the best Software as a Service (SaaS) provider

Abstract

Cloud computing (CC) provides dynamic computation services to offer a reliable and cost-effective cloud service to the customer. The selection of the best software as a service (SaaS) cloud services provider by ensuring considering various MCDM criteria (Cost, Ease of Use, Features and Functionalities, Security, Scalability, and Customer Support). For the selection of the best SaaS providers, we have considered Zoho CRM, Google Workspace, Microsoft 365, Slack, Asana, Dropbox, Shopify, Zoom, and AWS for evaluating the service consistency and high accuracy. The Multi-Criteria Decision Making (MCDM) provides a platform for selecting the best SaaS based on Quality of Service(QoS). Therefore, the proposed work has introduced a novel Bhattacharya and Cosine operator-based enhanced Trapezoidal Bipolar Fuzzy Analytic Hierarchy Process (AHP) with the Technique for Order of Preference by Similarity to Ideal Solution (Topsis) based decision-making for selecting the best SaaS. Thus, the proposed method minimizes the complexity of decision-making in uncertain scenarios. The Python-based experimental tool is utilized to evaluate the effectiveness of the proposed with the conventional techniques. Moreover, the case study and the sensitivity analysis prove the SaaS adoption while ensuring the robustness and stability of the suggested work.