Decentralized metal sorting yards: The engine-bottleneck paradox in circular supply chains

This study develops and applies an integrated Fuzzy SWARA–Fuzzy TOPSIS multi-criteria decision-making (MCDM) framework to evaluate decentralized metal sorting yards as meso-level intermediaries in circular supply chains, providing structured comparative assessment of yard types as upstream supplier segments within circular procurement systems. Using expert elicitation and triangular fuzzy numbers (TFNs) to accommodate linguistic uncertainty inherent in informal supply contexts, Fuzzy SWARA derives criteria weights through sequential comparative judgments across twelve operational, infrastructural, and governance-related criteria. Fuzzy TOPSIS then ranks three representative yard archetypes: urban micro-yards (A1), rural aggregation nodes (A2), and mobile aggregators (A3) based on their weighted proximity to an ideal supplier profile. SWARA reveals that contamination control and sorting purity (C2, weight = 0.503) and material identification accuracy (C1, weight = 0.252) together account for 75.5% of the total criteria weight. TOPSIS assigns closeness coefficients of 0.799 (A2), 0.490 (A1), and 0.150 (A3), identifying rural aggregation nodes as the highest-performing yard type and empirically confirming the engine–bottleneck paradox. To build on this exploratory model, future studies should use SEM for empirical validation and longitudinal research to monitor how these strategic priorities evolve dynamically. Buyers should prioritize rural aggregation nodes as preferred sourcing partners and engage urban micro-yards through targeted supplier development programs focused on contamination control and grading standardization. This study offers the first integrated Fuzzy SWARA–Fuzzy TOPSIS evaluation framework applied specifically to decentralized sorting yards as distinct supplier archetypes within circular supply chains, extending purchasing and supply management (PSM) scholarship to informal meso-level circular intermediaries. Novelty and research gap: To the best of our knowledge, this study offers the first integrated Fuzzy SWARA-Fuzzy TOPSIS evaluation framework applied specifically to decentralized metal sorting yards as distinct supplier archetypes within circular supply chains. The principal research gap addressed is the absence of structured, uncertainty-aware decision support for comparing heterogeneous yard types as upstream supplier segments in circular procurement systems. The methodological novelty lies in applying fuzzy weight elicitation to the informal sorting yard context where expert linguistic judgment is the primary data source, operationalising the engine-bottleneck paradox as a quantifiable supplier performance construct.