From performance ranking to defensible prioritization: an evidence- and stability-aware fuzzy MCDM framework for circular supply-chain strategies

Circular supply-chain strategy selection is not only a multi-criteria ranking problem, but also an evidential defensibility problem. Conventional fuzzy MCDM models represent expert uncertainty and preference ambiguity, yet the support behind different assessments and the stability of the resulting ranking are not always carried into the final recommendation logic. This study proposes an Evidence-Maturity and Stability-Adjusted Fuzzy Multi-Criteria Decision-Making (EM-SA-FMCDM) framework for prioritizing circular supply-chain strategies under heterogeneous evidence conditions. The framework records evidence support through an Evidence Maturity Index (EMI), refines uncertainty representation and criterion weighting, and incorporates evidence, proximity, and dispersion diagnostics into a conservative recommendation layer. The method is demonstrated using five experts, six strategies, and eight criteria. Conventional weighting places recycling/material-recovery partnerships (A4) marginally first, whereas support-aware weighting shifts the performance leader to design for circularity/disassembly (A6; 0.821 versus 0.817 for A4). The EM-SA configuration ranks A4 first (0.728) and closed-loop supplier collaboration (A2) second (0.699). Across the 30-scenario β–α grid, A6 leads all six settings with α = 0, whereas A4 leads all 24 settings with α > 0. Fuzzy TOPSIS and VIKOR retain method-dependent ordering near the top alternatives. The framework makes the transition from performance ranking to evidence- and stability-aware prioritization explicit.