Abstract: Migration flows are determined by both place-specific attributes and spatial interactions between origin and destination locations. However, conventional gravity models often struggle to disentangle these effects—specifically, the spatial interaction component, which is typically proxied by distance and remains the most challenging aspect to model, thereby hindering theoretical interpretation. Drawing on migration flow decomposition and structural gravity model theory, this study replaces the one-step "flow-variable" approach with a two-step "flow-effect-variable" framework. Using interprovincial migration data from China’s 6th and 7th population censuses, we decompose migration flows into spatial influence (origin), attractiveness (destination), and spatial interaction components to analyze their temporal trends. Building on these metrics, we employ multiple regression analysis to interpret the factors shaping spatial interactions, with a specific focus on the relationship between bilateral explanatory variables and spatial structure effects.