Coal Mine Safety Resilience via R4 Framework and Entropy-TOPSIS-GRA: A Decade of U.S. MSHA Data

Assessing mine-level safety resilience is critical for risk governance, yet organizational resilience constructs are difficult to quantify from routine regulatory records. Eight indicators computed from U.S. MSHA open data operationalize the R4 resilience framework (Robustness, Redundancy, Resourcefulness, and Rapidity) for coal mine safety. The panel spans 1276 mines and 5554 mine-year observations from 2014 to 2023. A sequential entropy-TOPSIS-GRA pipeline assigns objective weights, ranks mine-year resilience, and identifies the indicators most closely associated with the composite score. Production efficiency absorbed 47.75% of the entropy weight, and inspection frequency accounted for 25.16%, together accounting for approximately 73% of the total weight. At the rank-order level, inspection frequency (ρ = 0.660) and remediation rapidity (ρ = 0.539) tracked resilience positions most closely, while production efficiency showed a near-zero Spearman correlation (ρ = 0.038) despite its dominant weight. A structural mirror between violation rate and production efficiency (Spearman ρ = −0.967) was diagnosed and corrected in a series of robustness checks, after which inspection frequency and remediation rapidity retained the top ranks. Aggregate resilience scores held stable across three regulatory periods (Kruskal–Wallis p = 0.064), and the composite index aligned with external safety outcomes in a severity-graded fashion, with higher-scoring mine-years showing milder injuries conditional on accident occurrence. When indicators are scale-dependent, entropy-weighted composites require rank correlation analysis to separate size-driven variance from genuine safety influence. The framework offers regulators and operators a reproducible, open-data-based resilience proxy for monitoring the safety resilience of large mine panels.