A tendency coefficient–driven Pythagorean fuzzy distance approach for selection problems in higher education and medical waste management

Selection problems arising in higher education admissions and medical waste management are inherently affected by uncertainty, imprecision, and hesitation, which complicate reliable decision analysis. Pythagorean fuzzy sets provide a flexible mathematical framework for modeling such uncertainties, and a variety of Pythagorean fuzzy distance measures have been developed for decision-making applications. Nevertheless, existing distance measures overlook the role of tendency coefficients, which are necessary for characterizing the inclination and relative influence of Pythagorean fuzzy parameters and for enhancing the discriminatory power of distance-based methods. In this paper, a novel Pythagorean fuzzy distance measure incorporating tendency coefficients of the complete Pythagorean fuzzy parameters is proposed. The mathematical properties of the proposed distance measure are established to ensure its validity and consistency. To demonstrate its applicability, the proposed measure is integrated into a multi-criteria decision-making framework and applied to the evaluation of students’ examination scores for higher education admission. In addition, the technique for order of preference by similarity to the ideal solution is employed to address the selection of medical waste management systems under a Pythagorean fuzzy environment. Comparative studies with existing Pythagorean fuzzy distance measures confirm the improved effectiveness, stability, and reliability of the proposed approach in handling uncertainty and supporting robust decision-making.