Spatial Heterogeneity and Scale-Dependent Determinants of Public EV Charging Station Utilization: An Integrated Semantic-Spatial Approach

Abstract The growing gap between the rapid expansion of public electric vehicle (EV) charging infrastructure and its realized utilization efficiency poses a critical challenge to sustainable urban mobility. Existing studies’ reliance on macrolevel aggregates or single-dimensional metrics fails to capture fine-grained spatial heterogeneity or disentangle the interacting multiscale mechanisms that drive charging demand. This study proposes an integrated semantic–spatial analytical framework to quantify the determinants of utilization at the subdistrict scale. Using a multisource dataset for Beijing, China, we first identify urban functional zones through a Word2Vec-based semantic classification approach. We then combine the Optimal Parameter Geodetector and multiscale geographically weighted regression (MGWR) to detect dominant factors, interaction effects, and scale-dependent spatial relationships. The results show that charging station utilization is jointly shaped by demand intensity, urban functional context, and charging-supply configuration rather than by facility supply alone. A larger number of charging stations does not necessarily correspond to higher utilization. The subdistrict functional zone is the strongest explanatory factor, indicating that semantic urban context is a core determinant of charging performance. Several factor pairs, especially enterprise density coupled with fast charging availability, and housing price coupled with slow charging accessibility, exhibit strong nonlinear enhancement effects. MGWR better captured spatial nonstationarity ( R 2 of 0.661 versus 0.556 for GWR and 0.459 for OLS) and revealed distinct spatial scales of influence, separating near-global effects (e.g., population density) from locally varying coefficients and interaction patterns. These findings support a scale-sensitive, precision-oriented planning approach for optimizing the spatial allocation of urban charging infrastructure.