MCDM approach integrating q-rung orthopair fuzzy sets and social network analysis for ranking UPI digital payments in India: a case study

This paper proposes a novel approach to rank popular digital payment apps in India based on multiple criteria, such as user experience, security, and overall industry impact. To achieve this, we adopt multiple criteria decision-making (MCDM) methodologies, using q-rung orthopair fuzzy sets (q-ROFS) as the input range. The use of q-ROFS enhances the flexibility, resilience, and appropriateness of our model, surpassing intuitionistic fuzzy sets (IFS) and Pythagorean fuzzy sets (PFS). Incorporating the social network aspect, we account for trust relationships between experts, influencing decision-making. The weights assigned to each expert are determined through the Jaccard similarity measure. To further enhance our model's robustness, we adopt the entropy weight method (EWM) for determining criteria weights. The paper leverages the Digital India program, a flagship initiative of the Indian government, aimed at transforming India into a digitally empowered society and knowledge economy. With a significant increase in players in the UPI (Unified Payment Interface) market, it is imperative to have a transparent and useful ranking system to address intense competition. A comprehensive case study validates the proposed approach, evaluating the effectiveness of digital payment apps in India.