Stability analysis and control strategy of industry chain network from the perspective of risk transmission

Purpose Industry chain risk prevails among node enterprises, seriously affecting the chain’s overall stability. This study investigates the stability of the industry chain network from a risk transmission perspective to determine effective control strategies to address potential risk in the industry chain and ensure the stable development of the industry chain network. By incorporating novel perspectives and advanced tools, we propose risk control strategies that provide scientific decision-making support for industry chain managers. Design/methodology/approach To seek more effective risk control strategies, this study constructs an improved SEIRDS risk transmission model for the industry chain network by introducing the market elimination rate and enterprise entry rate. The model divides node enterprises into five states (S, E, I, R and D) to simulate the risk transmission process. Corresponding risk control strategies are then proposed, and their effects under a stable risk transmission state are analyzed to provide a decision-making reference for industry chain risk management. Findings The results show that risk transmission will lead to the industry chain network eventually converging into two states: risky and risk-free stability. Recovered enterprises with risk resilience will ultimately become the main group. For the two stable states of the industry chain network, adopting targeted control strategies can effectively curb the spread of risk. Under specific parameters, the impact of the remediation strategy is superior to that of either the prevention or control strategy, thereby ensuring the long-term stable development of the industry chain. Originality/value Considering the lag of risk transmission in the industry chain network and the entry and exit of enterprises in the chain, this study examines the stability of the industry chain network under risk transmission and the effects of different risk control strategies under a stable risk state.