Risk propagation and vulnerability in the global industrial robot trade network: A cascading failure model with adaptive resilience

Industrial robots underpin intelligent manufacturing and high-end equipment systems, and the stability of their global trade network is directly related to the continuity of international manufacturing specialization. Existing studies mainly focus on structural evolution and centrality features, while offering insufficient explanation of how risk shocks diffuse along trade relations, why core-node failure triggers cascading effects, and whether adaptive buffering mechanisms exist. This study examines the global industrial robot trade network from 2000 to 2023 and develops an adaptive cascading failure model integrating local buffering, global risk-control potential, technological-industrial support, trade-relationship stability, and supply reallocation. Because trade data cannot separate domestic production, processing trade, and re-exports, the propagation results describe network vulnerability and scenario-based trade vulnerability. The results show that network expansion and densification have generated more complex risk transmission paths; simulated risk diffusion is not determined solely by trade scale but by structural position, accumulated import gaps, and substitution absorption capacity; and adaptive supply reallocation can reduce simulated infection scale in some scenarios but cannot fully eliminate cascading risks caused by core-hub failures. This study provides a new analytical framework for identifying critical risk sources, propagation paths, and resilience enhancement directions.