Confidence Level-Based Hamacher Aggregation Operators for Sustainable Furniture Supplier Selection Using p,q-Quasirung Orthopair Fuzzy Sets

Sustainable furniture supplier selection for a university is crucial to ensuring environmentally responsible, cost-effective, and socially ethical procurement. However, the decision-making process involves vague and imprecise data, making traditional approaches less effective. The notion of p,q- quasirung orthopair fuzzy sets (p,q- QOFSs ) offers a more effective structure for managing this type of uncertainty. Introducing confidence levels into the decision-making process enhances accuracy and practicality by incorporating expert reliability into evaluations. To address this, we propose confidence level-based Hamacher weighted averaging (geometric) aggregation operators for p,q- QOF sets. Utilizing these operators, a multi -criteria group decision-making ( MCGDM ) model is developed to facilitate supplier selection. The model is applied to a real-world scenario where three decision-makers evaluate four suppliers based on eight sustainability criteria. A comparative analysis with existing confidence level-based aggregation operators demonstrates the proposed method's effectiveness. Additionally, sensitivity analysis, conducted by varying parameter values, confirms the stability and robustness of the approach.