The construction industry is a major contributor to economic development in the United Arab Emirates (UAE); however, it simultaneously places considerable pressure on natural resources, energy systems, and construction and demolition waste management infrastructure. Despite national sustainability initiatives such as the Circular Economy Policy 2031 and Net Zero 2050, the implementation of circular supply chain (CSC) practices within the UAE construction sector remains fragmented and operationally inconsistent. Existing studies provide limited empirically grounded and context-specific decision-support approaches capable of prioritizing circular strategies while accounting for multidimensional sustainability trade-offs and interdependencies among influencing factors. To address this gap, this study develops and validates an integrated multi-criteria decision-making (MCDM) framework for evaluating and prioritizing CSC strategies in the UAE construction sector. The framework integrates Delphi, Analytic Hierarchy Process (AHP), Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Delphi established expert consensus on evaluation dimensions, AHP quantified hierarchical importance, DEMATEL identified causal relationships among sustainability criteria, and TOPSIS prioritized alternative CSC strategies. Expanded robustness and sensitivity analyses were further conducted to evaluate ranking stability under multiple weighting and alternative-removal scenarios. The findings indicate that environmental criteria received the highest hierarchical importance, while DEMATEL identified environmental and technological dimensions as dominant causal drivers within the CSC system. At the strategy level, Modular Prefabrication and Off-site Manufacturing (A2) emerged as the most preferred strategy with the highest TOPSIS closeness coefficient (CC = 0.841649), followed by BIM/IoT-enabled Material Traceability (A4) (CC = 0.581554), Construction and Demolition (C&D) Waste Recycling (A1) (CC = 0.36718), Green Procurement and Local Sourcing (A3) (CC = 0.349074) and Reverse Logistics and Take-back Systems (A5) (CC = 0.213104). Expanded sensitivity and alternative-removal analyses further demonstrated that the prioritization of A2 and A4 remained stable across multiple perturbation scenarios, confirming the robustness of the proposed decision-making framework. The study also fulfills its theoretical contribution by empirically differentiating between importance and causality-based appraisals in circular supply chain decision-making and by showing the usefulness of thoroughly integrated hybrid MCDM models in sparse and scarce data situations. In practice, the findings can be inferred to actionable recommendations for construction companies, supply chain management, and policy makers to align high-leverage circular drivers with strategic investments. Altogether, the suggested framework will provide a clear, high-quality, and context-sensitive decision-support tool to speed up the circular supply chain change in the UAE construction industry and similar emerging economies.
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Praveen Kumar T. (2026) studied this question.
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