Development of an outranking-oriented multiple-criteria decision model within q-rung orthopair fuzzy contexts

In the construction industry, sustainable supplier selection poses a complex decision-making challenge, marked by uncertainty and vagueness. To address this, an innovative ELimination Et Choice Translating REality (ELECTRE) I, II, and III framework within the q-rung orthopair fuzzy set (q-ROFS) environment is proposed. This approach introduces a novel q-ROFS score function that integrates membership, non-membership, and hesitation degrees, offering enhanced differentiation compared to existing functions. The methods simplify traditional ELECTRE outranking relations, reduce computational complexity, and provide both partial and complete rankings while maintaining logical consistency. The results demonstrate the practicality and efficiency of the suggested methodology. Furthermore, sensitivity and comparative analyses confirm the robustness of the developed approaches. This research enhances the q-ROFS ELECTRE methodology by enabling more nuanced preference expression and a streamlined decision process, thus advancing fuzzy decision-making. It also provides a reliable resource for decision-makers in the construction industry and beyond, improving operational efficiency and sustainability.