A modified TOPSIS algorithm for the assessment of sports quality in higher education using circular pythagorean fuzzy information

Higher education institutions experience difficulties in sports quality assessment because multiple qualitative and quantitative factors, including sports facilities and coaching abilities, combine with student participation and institutional backing. Standard assessment systems encounter challenges when measuring subjective phenomena found in quality assessment evaluations. This research introduces an improved version of the technique for order of preference by similarity to ideal solution (TOPSIS) based multi-criteria decision-making (MCDM) model that utilizes circular Pythagorean fuzzy sets (CPyFS) to effectively process imprecise expert judgments. The proposed model implements redesigned weight assignment and distance computation techniques for optimizing decision reliability. A practical investigation analyzes different key evaluation criteria for sports programs, including basketball, soccer, volleyball, tennis, and swimming, through consultation with a sports director, senior coach, and a student representative. According to the results, the swimming program leads all other programs in sports quality assessment. The proposed model performs better than conventional fuzzy MCDM methods through robust ranking results, precise findings, and rapid computational speed. The evaluation system delivers a dependable method that enables sports policymakers and administrators to maximize investment while increasing student involvement within higher educational settings.