Revolutionizing Decision-Making in E-Commerce and IT Procurement: An IVPNS-COBRA Linguistic Variable Framework for Enhanced Multi-Criteria Analysis

Real-world challenges in e-commerce strategy selection and IT supplier evaluation are inherently complex due to uncertainty and incomplete information, necessitating a multi-faceted approach for effective decision-making. Traditional single methods often fail to address these complexities adequately. To overcome this limitation, this research introduces an advanced methodology by integrating the Interval-Valued Pythagorean Neutrosophic Set (IVPNS) with the Comprehensive Distance-Based Ranking (COBRA) approach, enhancing the handling of indeterminate information related to truth, falsity, and uncertainty. IVPNS provides a robust mathematical framework for managing ambiguity, a common challenge in Multi-Criteria Decision-Making (MCDM) across various domains. Prior to this study, IVPNS lacked a linguistic variable—a crucial component for expressing human judgments. To bridge this gap, we enhance the IVPNS-COBRA framework by incorporating 5-point and 7-point linguistic scales, ensuring compliance with established IVPNS conditions. Additionally, we introduce two distance measures, Euclidean and Hamming distances, to refine alternative evaluations. The proposed IVPNS-COBRA method is validated through real-world applications, including the evaluation of three e-commerce development strategies (assessed against five criteria) and four IT supplier selection alternatives (evaluated using nine criteria). The results demonstrate the reliability of this MCDM model, providing decision-makers with a more precise and structured approach for selecting optimal e-commerce strategies and IT suppliers in complex environments.