A data-driven MCDM approach to evaluating sexual harassment factors in educational settings: integrating OrdPA-F with triangular intuitionistic fuzzy MARCOS methods
Abstract
This study investigates the influence of ordering factors on sexual harassment in educational settings and evaluates legislative initiatives designed to enhance the safety of female students in schools and universities. When used together in an MCDM framework, OrdPA-F and IF-MARCS make it easier to find many important parts. First, we use OrdPA-F to figure out the weights of the attributes. Then, we use the IF-MARCOS method to evaluate the ranked factors. Improvements in decision-making are achieved through the development of triangular intuitionistic fuzzy numbers for analytical purposes. This study employs Dombi aggregation operators to comprehensively assess the influence of these elements on school sexual harassment. This research proposes an organized, data-driven method to aid lawmakers in formulating effective solutions for reducing sexual harassment and enhancing safety in learning environments.
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