Assessing Eco-Efficiency of Building Materials Using Type-2 Fuzzy AHP–TOPSIS Framework

The construction sector urgently needs methods to identify building materials that are both structurally reliable and environmentally efficient. This paper addresses the scientific issue of eco-efficiency assessment under deep uncertainty in life cycle, cost, and performance data for structural concretes. The research objective is to develop a robust decision-support framework that can rank conventional and low-carbon concretes when expert judgements are imprecise, and environmental indicators vary across contexts. To this end, we propose an interval Type-2 fuzzy AHP–TOPSIS model in which criteria weights and material performances are represented as interval Type-2 triangular fuzzy numbers, with Karnik Mendel centroid type-reduction used to obtain weight intervals and type-reduced decision entries. An eco-efficiency index based on normalized life-cycle assessment indicators (GWP, CED, AP), cost, compressive strength, and service life is used as an external validation target. The framework is demonstrated on a detailed case study comparing OPC, PPC, GGBS, recycled-aggregate, fly-ash, and geopolymer concretes. Results show that geopolymer concrete is consistently the most eco-efficient option and OPC the least, with strong rank concordance between Type-2 TOPSIS closeness coefficients and the eco-efficiency index, and stable top/bottom rankings underweight-band and joint weight-FOU perturbations. Compared with crisp and Type-1 fuzzy AHP-TOPSIS approaches, the proposed model uniquely offers a coherent end-to-end Type-2 pipeline, preserves the footprint of uncertainty in both weighting and ranking, and provides clearer robustness diagnostics for eco-efficiency-oriented material selection.