• A life-cycle MADM framework integrates sustainability and construction time • Environmental, economic and social impacts assessed using LCA, LCC and S-LCA • Uncertainty addressed through Monte Carlo simulation and sensitivity analysis • Applied to modular hospital buildings in high-seismic urban environments • Steel modular systems achieve the most robust overall performance The rapid deployment and life-cycle performance of hospitals are critical in seismic-prone regions, where construction speed affects social resilience and access to healthcare services. This study proposes a decision-support framework that integrates life cycle assessment (LCA), life cycle cost (LCC), social life cycle (S-LCA), and temporal performance within a multi-attribute decision-making (MADM) approach. Criteria weights are determined using the Best–Worst Method (BWM), with expert-judgment consistency ratios verified to reduce subjectivity; alternative rankings are obtained via an ensemble of emerging MADM techniques (EDAS, MABAC, and MARCOS). The framework is applied to a reference hospital block derived from a real healthcare complex and evaluated under seismic conditions representative of Quito, Ecuador, comparing three prefabricated volumetric modular systems—reinforced concrete, hot-rolled steel, and a concrete–steel hybrid—against a conventional cast-in-place reinforced concrete alternative. Temporal performance is quantified via a normalized indicator, ET, which accounts for reduced construction duration and financial benefits from earlier operational start-up. Environmental, social, and economic uncertainties are addressed through Monte Carlo simulation and sensitivity analyses, based on a process-based comparative life-cycle approach using secondary data sources and indicator-based social assessment, rather than a fully exhaustive ISO-compliant life-cycle assessment. Hot-rolled steel modular systems demonstrate the best overall performance, significantly reducing environmental and social impacts and construction time, despite higher initial costs. Sensitivity analyses confirm that the ranking remains stable under parameter variations of ±15%. The proposed framework offers a replicable, transparent tool to support procurement, planning, and emergency decision-making for critical healthcare infrastructure in high-seismic areas.
Guaygua et al. (Wed,) studied this question.