Pythagorean fuzzy-based integration of ANP with TOPSIS -VIKOR-SAW techniques for hospital service quality evaluation

In the context of healthcare services, evaluating quality is often complicated by inherent uncertainties and complex interdependencies between criteria. To address these challenges, this research proposes a novel methodology utilizing the Pythagorean fuzzy framework for multi-criteria decision-making in hospital service quality assessment. The study integrates the Analytic Network Process (ANP) with SAW, TOPSIS, and VIKOR methods within this Pythagorean fuzzy environment. ANP is employed to accurately capture the interdependencies between criteria and feedback mechanisms, a capability that has been underutilized in the literature. This integrated approach enables a more precise calculation of criteria weights, which are then used by SAW, TOPSIS, and VIKOR to rank hospitals effectively. Comprehensive analysis, including sensitivity and comparative evaluations, demonstrate the reliability of the proposed methodology. Key findings indicate that the proposed approach offers enhanced accuracy and stability in hospital rankings compared to traditional methods. This research advances the field of hospital service evaluation by employing Pythagorean fuzzy techniques and integrating multiple decision-making methods.