脆弱性(计算)
级联故障
风险分析(工程)
构造(python库)
脆弱性评估
计算机安全
忽视
独创性
透视图(图形)
计算机科学
工程类
业务
心理学
社会心理学
创造力
程序设计语言
功率(物理)
人工智能
心理弹性
物理
精神科
电力系统
量子力学
作者
Pinsheng Duan,Jianliang Zhou
出处
期刊:Engineering, Construction and Architectural Management
[Emerald (MCB UP)]
日期:2021-12-01
卷期号:30 (3): 1037-1060
被引量:21
标识
DOI:10.1108/ecam-06-2021-0475
摘要
Purpose The construction industry is an industry with a high incidence of safety accidents, and the interactions of unsafe behaviors of construction workers are the main cause of accidents. The neglect of the interactions may lead to serious underestimation of safety risks. This research aims to analyze the cascading vulnerability of unsafe behaviors of construction workers from the perspective of network modeling. Design/methodology/approach An unsafe behavior network of construction workers and a cascading vulnerability analysis model were established based on 296 actual accident cases. The cascading vulnerability of each unsafe behavior was analyzed based on the degree attack strategy. Findings Complex network with 85 unsafe behavior nodes is established based on the collected accidents in total. The results showed that storing in improper location, does not wear a safety helmet, working with illness and working after drinking are unsafe behaviors with high cascading vulnerability. Coupling analysis revealed that differentiated management strategies of unsafe behaviors should be applied. Besides, more focus should be put on high cascading vulnerability behaviors. Originality/value This research proposed a method to construct the cascading failure model of unsafe behavior for individual construction workers. The key parameters of the cascading failure model of unsafe behaviors of construction workers were determined, which could provide a reference for the research of cascading failure of unsafe behaviors. Additionally, a dynamic vulnerability research framework based on complex network theory was proposed to analyze the cascading vulnerability of unsafe behaviors. The research synthesized the results of dynamic and static analysis and found the key control nodes to systematically control unsafe construction behaviors.
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