emergency logistics response capacity, regional heterogeneity, spatiotemporal evolution characteristics, entropy-weighted TOPSIS method, Markov chain, Public aspects of medicine, RA1-1270

Public emergencies have surged worldwide, highlighting the critical role of emergency logistics in disaster relief. This study evaluates the heterogeneity and spatiotemporal evolution characteristics of regional emergency logistics response capacity in China using the entropy-weighted TOPSIS method, Dagum Gini coefficient, kernel density estimation, and Markov chain analysis. The emergency logistics response capacities of 30 provinces and four major economic regions (Eastern, Central, Western, Northeastern) were assessed from 2012 to 2021. Key findings reveal: (1) Provincial emergency logistics response capacities improved significantly nationwide, yet regional imbalances remain pronounced. (2) Regional heterogeneity expanded, driven primarily by inter-regional disparities. (3) Temporal analysis shows steady growth across all economic regions without polarization, with the Eastern region achieving the highest mean capacity and growth rate. (4) Spatial evolution demonstrates continuity, as Markov chain analysis reveals gradual transitions between adjacent capacity levels but limited leapfrog development. Spatial factors exert dual effects: proximity to high-capacity regions facilitates upgrades for moderate-level areas, yet suppresses low capacity regions. These findings emphasize persistent structural gaps in infrastructure, resource allocation, and governance.