Cascading vulnerability analysis of unsafe behaviors of construction workers from the perspective of network modeling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pinsheng Duan ◽  
Jianliang Zhou
Keyword(s):  
Complex Network ◽  
Network Modeling ◽  
Vulnerability Analysis ◽  
Construction Workers ◽  
Cascading Failure ◽  
Failure Model ◽  
Analysis Model ◽  
Content Type ◽  
Unsafe Behavior ◽  
Unsafe Behaviors

PurposeThe 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.

scholarly journals Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach

2020 ◽  
Vol 17 (5) ◽  
pp. 1588 ◽  
Author(s):  
Gui Ye ◽  
Hongzhe Yue ◽  
Jingjing Yang ◽  
Hongyang Li ◽  
Qingting Xiang ◽  
...  
Keyword(s):  
Cognitive Process ◽  
Organizational Factors ◽  
Agent Based Modeling ◽  
Construction Workers ◽  
Obvious Effect ◽  
Agent Based ◽  
Cognitive Failure ◽  
Unsafe Behavior ◽  
Unsafe Behaviors ◽  
Social Organizational

Previous literature has recognized that workers’ unsafe behavior is the combined result of both isolated individual cognitive processes and their interaction with others. Based on the consideration of both individual cognitive factors and social organizational factors, this paper aims to develop an Agent-Based Modeling (ABM) approach to explore construction workers’ sociocognitive processes under the interaction with managers, coworkers, and foremen. The developed model is applied to explore the causes of cognitive failure of construction workers and the influence of social groups and social organizational factors on the workers’ unsafe behavior. The results indicate that (1) workers’ unsafe behaviors are gradually reduced with the interaction with managers, foremen, and workers; (2) the foreman is most influential in reducing workers’ unsafe behaviors, and their demonstration role can hardly be ignored; (3) the failure of sociocognitive process of construction workers is affected by many factors, and cognitive process errors could be corrected under social norms; and (4) among various social organizational factors, social identity has the most obvious effect on reducing workers’ unsafe behaviors, and preventive measures are more effective than reactive measures in reducing workers’ unsafe behaviors.

Knowledge discovery of correlations between unsafe behaviors within construction accidents

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shengyu Guo ◽  
Yujia Zhao ◽  
Yuqiu Luoren ◽  
Kongzheng Liang ◽  
Bing Tang
Keyword(s):  
Knowledge Discovery ◽  
Tacit Knowledge ◽  
The Body ◽  
Construction Workers ◽  
Frequent Pattern ◽  
Research Approach ◽  
Content Type ◽  
Railway Construction ◽  
Unsafe Behaviors ◽  
Construction Accidents

PurposeKnowledge discovery related to unsafe behaviors promotes the performance of accident prevention in construction. Although numerous studies on accident causation models have discussed the correlations of unsafe behaviors with various factors (e.g., unsafe conditions), limited research explores correlations between unsafe behaviors within accidents. The purpose of this paper is mining strong association rules of unsafe behaviors from historical accidents to clarify this kind of tacit knowledge.Design/methodology/approachA case study was adopted as the research approach, in which accident records from building and urban railway construction in China were selected as data resources. The groups of unsafe behaviors extracted from accident records were expressed by the definitions of unsafe behaviors from safety regulations and operating procedures. Frequent Pattern (FP)-Growth algorithm was used for association rule mining, and the critical correlations between unsafe behaviors were represented by the effective strong rules.FindingsThe findings identify and distinguish correlations between unsafe behaviors within construction accidents. In building construction, workers and managers should pay attention to preventing unsafe behaviors related to personal protective equipment and machines and equipment. In urban railway construction, workers should especially avoid unsafe behaviors of inadequately dealing with environmental factors.Practical implicationsTacit knowledge is transferred to explicit knowledge as the critical correlations between unsafe behaviors within accidents are determined by the effective strong rules. Additionally, the findings provide practice guidance for safety management, to collaboratively control unsafe behaviors with strong correlations.Originality/valueThis study contributes to the body of safety knowledge in construction and provides a further understanding of how construction accidents are caused by multiple unsafe behaviors.

The Simulation Optimization of Miners’ Unsafe Behavior Control Method

2019 ◽  
Vol 7 (2) ◽  
pp. 148-160
Author(s):  
Jiangshi Zhang ◽  
Hongyu Hao ◽  
Xue Li ◽  
Wenyue Zhang
Keyword(s):  
Safety Climate ◽  
Control Method ◽  
Influential Factors ◽  
Working Environment ◽  
Analysis Model ◽  
Safety Level ◽  
Unsafe Behavior ◽  
Unsafe Behaviors ◽  
Behavior Based ◽  
Safety Investment

Abstract Making optimal safety investment decisions are important for improving worker’s safety level and reducing accident frequency. To study the complex relationship between safety investment and miners’ behavior-based safety, we proposed the index system of the influential factors on miners’ unsafe behaviors and utilized system dynamics (SD) method to construct the analysis model. Based on the empirical research on a mining company in Hunan, miners’ behavior-based safety level under different investment conditions were simulated, then 12 kinds of schemes’ simulation were obtained. Finally, the optimal scheme was achieved. The scheme is: Safety cost per ton of coal is 3.8 dollars, investment proportion is: Organizational management (0.44), safety climate (0.16), working environment (0.08), technological equipment (0.32). This scheme reached the target value of 90 in the 28th month, which was 9 months shorter than that of the original one. The optimized results show that increasing the behavior-based safety investment and adjusting the proportion appropriately, can improve miners’ behavior-based safety level effectively.

Diagnostic intervention program based on construction workers' internal factors for persistent reduction of unsafe behavior

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mehdi Mohajeri ◽  
Abdollah Ardeshir ◽  
Hassan Malekitabar
Keyword(s):  
Intervention Program ◽  
Video Camera ◽  
Subjective Norms ◽  
Construction Workers ◽  
Camera System ◽  
Internal Factors ◽  
Content Type ◽  
Safety Attitudes ◽  
Unsafe Behavior ◽  
The Individual

PurposeThis study aims to show what interventions in human factors can effectively reduce construction workers' unsafe behavior.Design/methodology/approachA diagnostic intervention model targeted the construction workers' weakest internal factors. The workers' behavior and cognition data were collected via a questionnaire and a video camera system from two medium-sized construction sites. A safety supervisor accompanied each site supervisor to improve construction workers' internal factors by implementing the designed intervention measures.FindingsThe statistical analysis results confirmed a persistent positive effect on construction workers' safe behavior by improving internal factors. Among the intervention programs applied, those aimed to improve the subjective norms, safety knowledge and attitudes had the most significant effect sizes.Practical implicationsThe findings of this case study advise project managers to design a specific behavioral intervention that aims at improving construction workers' significant internal factors, including subjective norms, safety attitudes, habits and knowledge together with demographic characteristics to reduce construction workers' unsafe behavior.Originality/valueWhile the declining rate of construction accidents approaches an asymptote which is still high, this study suggests that targeting the individual internal factors through diagnostic interventions is the key to further reduce the rate by improving construction workers' behavior.

scholarly journals Relationship between Dimensions of Safety Climate and Unsafe Behaviors of the Construction Industry Workers

2021 ◽  
Author(s):  
Sara Tabanfar ◽  
Reza Pourbabaki ◽  
Seyvan Sobhani
Keyword(s):  
Standard Deviation ◽  
Construction Industry ◽  
Safety Climate ◽  
Workplace Safety ◽  
National Standards ◽  
Construction Workers ◽  
Cross Sectional ◽  
Unsafe Behavior ◽  
Unsafe Behaviors ◽  
The Relationship

Background: Construction industry has been ranked among the most dangerous industries worldwide due to the high number of accidents. The safety climate can be considered as a stimulus to reduce unsafe behaviors and thus reduction the accidents. This study was carried out to investigate the relationship between the dimensions of the safety climate and unsafe behavior of the construction workers in Tehran, Iran. Methods: The present study is a descriptive cross-sectional research on 90 construction workers. Unsafe behaviors recorded using the American National Standards Institute method and interviews with the workers. The Safety Climate was measured using the UK health care Safety Climate Questionnaire. The descriptive statistics (mean and standard deviation) were used to summarize the findings and the Pearson’s correlation coefficient was used to show the relationship between the variables. The SPSS software was used to analyze the data. Results: The mean and standard deviation of safety climate score and unsafe behavior were (3.98+ 0.27) and (45.93 + 17.3), respectively. There was a significant relationship between unsafe behaviors and staff knowledge (r = -0.31 and P = 0.004). We also found relationship between unsafe behavior and safety climate score (r = -0.21 and P = 0.043). Conclusion: The employees' knowledge was one of the most important components of workplace safety. Also, this component assigned itself the highest score, and increasing the score in this dimension of the safety climate can lead to reduction unsafe behavior. Finally, according to the results, as the safety climate among employees increases, unsafe behaviors will decrease, and productivity would be increase.

Cascading failure model in power grids using the complex network theory

2016 ◽  
Vol 10 (15) ◽  
pp. 3940-3949 ◽  
Author(s):  
Fan Wenli ◽  
Liu Zhigang ◽  
Hu Ping ◽  
Mei Shengwei
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Power Grids ◽  
Cascading Failure ◽  
Failure Model ◽  
Complex Network Theory

scholarly journals A Cascading Failure Model Considering Operation Characteristics of the Communication Layer

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 9493-9504
Author(s):  
Geng Zhang ◽  
Jiawen Shi ◽  
Shiyan Huang ◽  
Jiye Wang ◽  
Hao Jiang
Keyword(s):  
Cascading Failure ◽  
Failure Model ◽  
Communication Layer ◽  
Operation Characteristics

Scenario based evaluation of a cost risk model through sensitivity analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Practical Method ◽  
Cost Evaluation ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Content Type ◽  
Detailed Evaluation ◽  
Cost Risk

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

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