Data-driven resilience modeling: Shock response of Turkish logistics corridorss

Traditional transport planning often fails to manage changes in people's mobility during crises. This study uses data from Meta's "Data for Good" platform to analyse how well Türkiye's transportation network can deal with external shocks. The mobility of 81 provinces was modelled using K-Means clustering and validated through spatial analyses and a Logistics Dominance Index (LDI). Results identify four distinct functional zones. Large metropolises (Cluster 4) showed high vulnerability, while logistics corridors (Cluster 2) demonstrated operational robustness, showing +3.69% continuity during crisis periods. LDI results indicate that road capacity in these regions is predominantly influenced by commercial freight. Despite the presence of high functional resilience, significant spatial risks are identified due to geographical overlap with the North Anatolian Fault Line. The findings of the present study suggest that future planning should prioritise network redundancy and data-driven dynamic management over static capacity expansion.