A Hybrid SWOT-AHP-TOPSIS Framework for Sustainable Design-Build Contractor Selection in Public Building Procurement

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Public owners selecting design-build (DB) teams for sustainable buildings must justify how proposal evidence, long-term asset performance, and procurement accountability support a preferred contractor. Prior contractor-selection and hybrid MCDM studies provide criteria and ranking tools, but they rarely connect public-building requirements, mandatory floors, proposal evidence anchors, weighting, scoring, and auditability before mathematical ranking. The aim of this study is to develop and numerically demonstrate an evidence-traceable SWOT-AHP-TOPSIS framework for sustainable DB contractor selection in California courthouse procurement. Here, California courthouse procurement refers to public-owner procurement of judicial courthouse facilities in California, United States, under public-building procurement rules and publicly available RFQ/RFP-related records. The framework fixes source-linked criteria, SWOT role definitions, benefit directions, evidence anchors, and compliance floors before criteria weights are obtained using AHP and alternatives are ranked using the TOPSIS method. The proof of concept derives 16 criteria from procurement guidance, California courthouse records, and the literature; reports local and global criteria weights obtained using AHP; and compares synthetic proposal archetypes. Under baseline illustrative weights, A1 ranks first (C* = 0.6548), followed by A3 (0.5804) and A2 (0.3294). Robustness checks using the disclosed matrices show conditional stability: vector, min–max, and linear-sum TOPSIS, equal-criterion weights, weighted-sum comparison, grouped +20% scenarios, comparison-set checks, and 10,000-run Monte Carlo perturbation retain A1 most frequently. The Monte Carlo run selected A1 first in 79.80% of simulations, A3 in 20.19%, and A2 in 0.01%, with top-two practical ties in 7.10% of runs. The results demonstrate arithmetic consistency, reproducibility, and interpretable ranking behavior under stated synthetic assumptions; they do not establish actual evaluator preferences, real proposal quality, award outcomes, or generalizability beyond California courthouse settings.