Research on risk propagation mechanism and control strategy of prefabricated building supply chain: based on complex network model and dynamic simulation analysis

Purpose As the construction industry transforms towards green and low-carbon development, prefabricated buildings (PBs) have become the mainstream trend of industry development with their significant advantages of environmental protection, high efficiency and resource conservation. However, the prefabricated building supply chain (PBSC) faces many risks and challenges in actual operation, which pose a serious threat to the stability and sustainable development of the supply chain (SC). Taking the PB project of Enterprise J as an example, this paper deeply explores the risk propagation mechanism in its SC and proposes a practical risk control strategy, aiming to enhance the risk resistance and resilience of the SC and ensure its sustainable development. Design/methodology/approach Based on the actual contract data of Enterprise J, this study constructed a four-layer PBSC network model, covering PB contractors, material suppliers, module manufacturers, and PB construction enterprises. By identifying and evaluating the main risk factors in the SC, combined with the improved Criteria Importance Through Intercriteria Correlation method and the cloud-matter element evaluation model, the weight and vulnerability of each risk factor were analyzed. MATLAB R2022b software was further used to simulate the Susceptible-Infected-Recovered-Susceptible (SIRS) model to analyze the impact of different risk control strategies on risk propagation. Findings This study analyzed the PBSC network of J Company and found that it has high connectivity and low group characteristics, which promotes the rapid spread of risks. SIRS model analysis shows that the infection rate is most sensitive to risk transmission, and a higher infection rate accelerates the spread, emphasizing the importance of controlling the initial infection rate. The recovery rate significantly affects the speed of risk transmission, while the immune extinction rate affects the long-term stability of the SC. The betweenness centrality strategy based on betweenness centrality performs well in controlling risk transmission, and can effectively reduce the number of infected enterprises and shorten the recovery time. The study also found that PB contractors and material suppliers are key links and are prone to become the source of risk transmission; while module manufacturers and PB construction enterprise show strong risk resistance. Practical implications This study provides a new theoretical framework and practical strategy for risk management of PBSC of enterprise J, helping enterprises to identify key risk nodes and effectively control risk propagation through reasonable immunization strategies, thereby enhancing the stability and resilience of the SC. The research results provide strong support for coping with external uncertainties and technological changes, and promote the healthy development of enterprise J. Originality/value This study takes the PBSC network of J Company as an empirical object, deeply analyzes its risk propagation mechanism and control strategy, and has significant academic innovation and practical value. By constructing a four-layer weighted directed network model that conforms to the actual operation of the enterprise, and combining the SIRS model for dynamic simulation analysis, this study reveals the key impact of infection rate, recovery rate and immune extinction rate on SC risk propagation, and provides a new perspective and theoretical basis for J Company’s SC risk management. In particular, the betweenness immunization strategy based on betweenness centrality, as an innovative solution, provides a practical path for enterprises to identify and control key risk nodes. The study also further analyzes the vulnerability and recovery capacity of different levels, and proposes targeted strategies to enhance the resilience and risk resistance of the enterprise SC. This study not only enriches the theoretical framework of J Company’s SC risk management, but also provides an operational practical guide for it to improve the stability of the SC and cope with the challenges of external uncertainty.