Abstract: To investigate how higher-order network structures and enterprise heterogeneity in risk attitudes and risk control effectiveness jointly influence the propagation of supply chain disruption risks, this study develops a tri-layer simplicial-complex-based coupled propagation model. In this framework, the diffusion of risk-warning information, the adoption of risk-control measures, and the propagation of disruption risks are respectively modeled as three interdependent layers of simplicial-complex networks. Specifically, the information diffusion layer captures how risk warnings spread across supply chain partners; the behavior adoption layer describes enterprises’ decision-making regarding the implementation of risk-control measures; and the disruption spreading layer characterizes the transmission mechanism of disruption risks within supply chain networks. The microscopic Markov chain approximation (MMCA) method is employed to conduct theoretical analysis, and a series of numerical simulations are performed to examine the effects of higher-order network structures and heterogeneous enterprise attributes on the coupled spreading dynamics. The results demonstrate that high-order network structures can substantially accelerate the spread of disruption risks and enlarge the steady-state disruption scale, while exhibiting a persistent initial-condition–sensitive bistability across different initial disruption levels. Enhancing firms’ risk-aversion levels effectively suppresses disruption propagation; however, its mitigation effect depends on the consistency of firms’ behavioral responses, and excessive heterogeneity in risk attitudes weakens the overall spillover benefits of preventive actions. Strengthening the effectiveness of risk-control measures also helps reduce disruption density, but when the effectiveness of such measures varies too widely, firms with weaker control capacities become structural weak points in the network, causing the system-wide suppression capability to decline as heterogeneity increases.

Key words: supply chain network, disruption risk propagation, higher-order network structure, enterprise heterogeneity