Identification of Key Risk Nodes and Invulnerability Analysis of Construction Supply Chain Networks

被引:3
作者
Wang, Hongchun [1 ]
Zhou, Zixiang [1 ]
机构
[1] Beijing Univ Civil Engn & Architecture, Sch Urban Econ & Management, Beijing 102616, Peoples R China
基金
中国国家自然科学基金;
关键词
construction supply chain; invulnerability; key node; risk management; cascading failure; complex network theory;
D O I
10.3390/buildings14071997
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The construction supply chain confronts interruption risks that raise significant concerns regarding industry safety and stability. Consequently, exploring risk management strategies from both enterprise and supply chain network perspectives is crucial. This study employs complex network theory and the cascade failure model to propose a methodology tailored to the unique characteristics of the construction supply chain, facilitating the identification of key risk nodes and the conduct of invulnerability analyses. By evaluating the importance of construction enterprise nodes and their risk propagation ability during cascade failures, this method enables the comprehensive identification of key risk node enterprises within the construction supply chain network. Furthermore, this study examines and discusses strategies for enhancing network invulnerability by taking into account node capacity, load, and resilience. Empirical results indicate that the key nodes and risk nodes in the construction supply chain network are mainly located upstream and downstream, displaying specific distribution patterns. In addition to core enterprises, key risk nodes comprise some strong suppliers at the intermediary and lower tiers of the supply chain. Adjustments to node enterprise parameters like capacity, load, and resilience have diverse impacts on the invulnerability of the construction supply chain network. This study clarifies the distribution patterns of key risk nodes within the construction supply chain network and the variations in network invulnerability under particular conditions, providing valuable insights for risk management decision-making.
引用
收藏
页数:18
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