Grading green building materials: A hyperbolic fuzzy framework for a sustainable hospital

Sustainable hospitals require careful selection of green building materials (GBMs) to reduce eco-impact and improve resilience. This is crucial as hospitals consume significant resources and their material choices influence durability, availability, and indoor air quality. Existing studies did not model uncertainty effectively, calculate experts’ weights methodically, and determine personalized/combined ranks of GBMs. This paper aims to address these gaps by developing an integrated decision framework that evaluates factors/criteria, assigns importance values, and ranks GBMs systematically. The methodology combines hyperbolic fuzzy data with attitudinal variance, LOPCOW, and choice-based WISP methods to determine experts’ weights, factor importance, and material grades. The proposed rank algorithm produces both personalized and cumulative grades. Results show durability, material availability, and indoor air quality as the top three factors, with hempcrete, cross-laminated timber, and rammed earth as the leading GBMs. This framework contributes by offering stakeholders a rational, uncertainty-resilient tool for sustainable hospital design.