Exploring the Digital Economy and Green Logistics Nexus in China: Evidence from 120 Logistics Hub Cities

The integration of the digital economy (DE) and green logistics (GL) is increasingly recognized as a critical pathway for modernizing logistics systems and achieving carbon neutrality. However, their spatiotemporal synergy remains underexplored. Utilizing panel data from 120 logistics hub cities (LHC) in China from 2013 to 2022, this study constructs a comprehensive framework to evaluate the coupling coordination degree (CCD) between DE and GL. We employ the Dagum Gini coefficient to dissect spatial disparities and integrate the CatBoost algorithm with SHapley Additive exPlanations (SHAP) to unravel the driving mechanisms of this coordination. The results reveal that: (1) The overall CCD in Chinese LHC exhibits a consistent upward trajectory, yet spatial development remains highly uneven, forming a distinct hierarchical spatial pattern. (2) Spatial disparities in the integration level have widened over time, with transvariation density constituting the primary source of overall inequality. (3) The CatBoost-SHAP analysis identifies urban economic density, urbanization level, advanced industrial structure, and human capital level as the paramount drivers. These findings enrich existing literature by providing nuanced, data-driven insights for policymakers to leverage digitalization, formulate spatially differentiated strategies, and foster sustainable logistics networks.