Group decision-making framework utilizing interval-valued intuitionistic fuzzy extended VIKOR methodology with applications in software quality assessment

Software quality evaluation (SQE) plays a critical role in software development, requiring decision-making across multiple factors. As decision-making scenarios become more complex, researchers have increasingly focused on group decision-making (GDM) models. Key tasks in GDM include determining expert weights and assessing the closeness between decision matrices. This study introduces a new GDM framework for multi-attribute decision-making using interval-valued intuitionistic fuzzy (IVIF) evaluation information. The proposed method begins with a novel normalized projection measure to evaluate the proximity between two IVIF matrices. Based on this measure, a technique is developed for calculating expert weights and enhancing the VlseKriterijumska Optimizacija Kompromisno Resenje (VIKOR) methodology. The framework integrates group utility, regret, and satisfaction measures, and is applied to a case study on SQE to evaluate its effectiveness through both static and dynamic experiments. A dynamic data testing approach is also introduced to further demonstrate the superior performance of the proposed framework. Results show that the method outperforms existing approaches in terms of robustness, stability, and comprehensiveness. The study’s findings provide valuable insights into software quality management and offer practical implications for organizational applications. Furthermore, the method’s applicability extends beyond SQE, offering new perspectives and benchmarks for decision-making research in diverse domains.