Access the full text.
Sign up today, get DeepDyve free for 14 days.
Shengyu Guo, Bing Tang, Kongzheng Liang, Xinyu Zhou, Ji-chao Li (2021)
Comparative Analysis of the Patterns of Unsafe Behaviors in Accidents between Building Construction and Urban Railway ConstructionJournal of Construction Engineering and Management-asce, 147
Zhipeng Zhou, J. Irizarry, Qiming Li (2014)
Using Network Theory to Explore the Complexity of Subway Construction Accident Network (SCAN) for Promoting Safety ManagementSafety Science, 64
N. Khakzad, G. Reniers (2015)
Using graph theory to analyze the vulnerability of process plants in the context of cascading effectsReliab. Eng. Syst. Saf., 143
Wei-Xin Jin, Ping Song, Guo-Zhu Liu, H. Stanley (2015)
The cascading vulnerability of the directed and weighted networkPhysica A-statistical Mechanics and Its Applications, 427
Shengyu Guo, Yujia Zhao, Yuqiu Luoren, Kongzheng Liang, Bing Tang (2021)
Knowledge discovery of correlations between unsafe behaviors within construction accidentsEngineering, Construction and Architectural Management
C. Lam, M. Fuse, T. Shimizu (2019)
Assessment of risk factors and effects in hydrogen logistics incidents from a network modeling perspectiveInternational Journal of Hydrogen Energy
Jun-qiang Leng, Jingjing Zhai, Qianwen Li, Lin Zhao (2018)
Construction of road network vulnerability evaluation index based on general travel costPhysica A-statistical Mechanics and Its Applications, 493
Ning-sheng Guo, P. Guo, Haiyong Dong, Jing Zhao, Qingye Han (2019)
Modeling and analysis of cascading failures in projects: A complex network approachComput. Ind. Eng., 127
Yingying Xing, Jian Lu, Shengdi Chen, S. Dissanayake (2017)
Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai MetroPublic Transport, 9
M. Mohajeri, A. Ardeshir, M. Banki, H. Malekitabar (2020)
Discovering causality patterns of unsafe behavior leading to fall hazards on construction sitesInternational Journal of Construction Management, 22
Shengyu Guo, Xinyu Zhou, Bing Tang, Peisong Gong (2020)
Exploring the behavioral risk chains of accidents using complex network theory in the construction industryPhysica A-statistical Mechanics and Its Applications, 560
Yanbo Che, Jingjing Jia, Yuancheng Zhao, Dongzi He, Tianwei Cao (2019)
Vulnerability assessment of urban power grid based on combination evaluationSafety Science
Staffan Larsson, A. Pousette, Marianne Törner (2008)
Psychological climate and safety in the construction industry-mediated influence on safety behaviourSafety Science, 46
Bingchun Wang, Zhirui Zhang, Xiaogang Qi, Lifang Liu (2019)
Identify Critical Nodes in Network Cascading Failure Based on Data AnalysisJournal of Network and Systems Management, 28
Yongliang Deng, Qiming Li, Ying Lu (2015)
A Research on Subway Physical Vulnerability Based on Network Theory and FMECASafety Science, 80
Weiwei Wu, A. Gibb, Qiming Li (2010)
Accident precursors and near misses on construction sites: An investigative tool to derive information from accident databasesSafety Science, 48
Yingbin Feng, Peng Wu, Gui Ye, Dong Zhao (2017)
Risk-Compensation Behaviors on Construction Sites: Demographic and Psychological DeterminantsJournal of Management in Engineering, 33
Zhipeng Zhou, J. Irizarry (2016)
Integrated Framework of Modified Accident Energy Release Model and Network Theory to Explore the Full Complexity of the Hangzhou Subway Construction CollapseJournal of Management in Engineering, 32
Mengchun Zhang, D. Fang (2013)
A cognitive analysis of why Chinese scaffolders do not use safety harnesses in constructionConstruction Management and Economics, 31
A. Motter, Y. Lai (2002)
Cascade-based attacks on complex networks.Physical review. E, Statistical, nonlinear, and soft matter physics, 66 6 Pt 2
Hongyu Chen, Limao Zhang, L. Qiong, Wang Hongtao, Dai Xiaosong (2021)
Simulation-based vulnerability assessment in transit systems with cascade failuresJournal of Cleaner Production, 295
Cheng Zhou, Chen Rui, Shuangnan Jiang, Ying Zhou, L. Ding, M. Skibniewski, Lin Xinggui (2019)
Human dynamics in near-miss accidents resulting from unsafe behavior of construction workersPhysica A: Statistical Mechanics and its Applications
Mengjie You, Shuang Li, Dingwei Li, Qing Xia (2019)
Study on the Influencing Factors of Miners’ Unsafe Behavior PropagationFrontiers in Psychology, 10
G. Andreotti, C. Lai (2019)
Use of fragility curves to assess the seismic vulnerability in the risk analysis of mountain tunnelsTunnelling and Underground Space Technology
Keping Li, Shanshan Wang (2018)
A network accident causation model for monitoring railway safetySafety Science
Shengyu Guo, Pan Zhang, L. Ding (2019)
Time-statistical laws of workers’ unsafe behavior in the construction industry: A case studyPhysica A: Statistical Mechanics and its Applications
Yu Zeng, R. Xiao (2014)
Modelling of cluster supply network with cascading failure spread and its vulnerability analysisInternational Journal of Production Research, 52
S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, D. Hwang (2006)
Complex networks: Structure and dynamicsPhysics Reports, 424
Jingjing Yang, Gui Ye, Qingting Xiang, Minkoo Kim, Qinjun Liu, Hongzhe Yue (2021)
Insights into the mechanism of construction workers’ unsafe behaviors from an individual perspectiveSafety Science, 133
Zhipeng Zhou, J. Irizarry, Wenya Guo (2021)
A network-based approach to modeling safety accidents and causations within the context of subway construction project managementSafety Science
John Bohm, D. Harris (2010)
Risk Perception and Risk-Taking Behavior of Construction Site Dumper DriversInternational Journal of Occupational Safety and Ergonomics, 16
Journal of Safety Science and Technology, 14
Xiaopeng Deng, Low Pheng, Xianbo Zhao (2014)
Project System Vulnerability to Political Risks in International Construction Projects: The Case of Chinese ContractorsProject Management Journal, 45
T. Aven (2007)
A unified framework for risk and vulnerability analysis covering both safety and securityIEEE Engineering Management Review, 39
R. Albert, A. Barabási (2001)
Statistical mechanics of complex networksArXiv, cond-mat/0106096
Jianhua Zhang, Meng Wang (2019)
Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metroPhysica A-statistical Mechanics and Its Applications, 535
Jianwei Wang, Lili Rong, Liang Zhang, Zhongzhi Zhang (2008)
Attack vulnerability of scale-free networks due to cascading failuresPhysica A-statistical Mechanics and Its Applications, 387
Weili Fang, P. Love, Hanbin Luo, L. Ding (2020)
Computer vision for behaviour-based safety in construction: A review and future directionsAdv. Eng. Informatics, 43
Coal Economic Research, 38
J. Stratman, Carolyn Youssef-Morgan (2019)
Can positivity promote safety? Psychological capital development combats cynicism and unsafe behaviorSafety Science
Zhongming Jiang, D. Fang, Mengchun Zhang (2015)
Understanding the Causation of Construction Workers’ Unsafe Behaviors Based on System Dynamics ModelingJournal of Management in Engineering, 31
(2019)
Census of fatal occupational injuries summary, 2019
M. Barthelemy, A. Barrat, R. Pastor-Satorras, Alessandro Vespignani (2004)
Characterization and modeling of weighted networksPhysica A-statistical Mechanics and Its Applications, 346
R. Albert, Hawoong Jeong, A. Barabási (2000)
Error and attack tolerance of complex networksNature, 406
Ning-sheng Guo, P. Guo, Ravi Madhavan, Jingrui Zhao, Yang Liu (2020)
Assessing the Vulnerability of Megaprojects Using Complex Network TheoryProject Management Journal, 51
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/approachAn 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.FindingsComplex 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/valueThis 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.
Engineering Construction & Architectural Management – Emerald Publishing
Published: Apr 4, 2023
Keywords: Cascading failure; Complex network; Construction workers; Unsafe behavior; Vulnerability
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.