Supply Chain Risk Propagation Model Based on Double-Layer Dynamic Evolution Network

Abstract

Aiming at the risk propagation problem in the evolution of the supply chain, this paper proposes a two-layer dynamic evolution model under the vision of hyper-network. The upper layer of the model is the social network described by the hyper-network, and the lower layer of the model is the supply chain risk propagation layer described by an activity-driven network. Considering the impact of warning information on the supply chain risk propagation, by using the Micro-Markov Chain Approach, a detailed theoretical analysis is carried out on the number of links and the inter-layer parameters of the model. The simulation results show that several links to the nodes on the risk propagation layer and the infection rate promote risk propagation, the influence parameters of the information layer on the risk layer and the recovery rate inhibit the spread of risk. The correctness of the theoretical analysis and the reliability of the model are further verified by Matlab simulation.