Investigation of the causality patterns of non-helmet use behavior of construction workers

Li, Heng; Li, Xiaoying; Luo, Xiaochun; Siebert, Joanna

doi:10.1016/j.autcon.2017.02.006

Cited by 62 publications

(27 citation statements)

References 33 publications

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“…For human risk factors, a part of them are due to the objective conditions or capabilities of participants caused by information symmetry, such as the contractor's technical capability; however, a part of risk factors is still caused by information asymmetry, and could lead to moral hazard and adverse selection in order to obtain more benefit. The risk factors based on information asymmetry are referred to as the behavioral risk of the principal participants [23][24][25].…”

Section: Behavioral Risk In the Construction Industrymentioning

confidence: 99%

Critical Behavioral Risk Factors among Principal Participants in the Chinese Construction Industry

Pan

Jia

2018

Sustainability

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The main participants in construction projects are the client, contractors, material suppliers, and consultants such as the project supervisor. They play the most important roles in implementing construction projects, and their behavior has a significant impact on the project’s performance. Because each participant has their own particular interests, by virtue of proprietary information advantage, each individual participant is driven to achieve maximum benefit, which can result in improper behavior with respect to each other. The risk of this resulting in moral hazard and adverse selection based on information asymmetry is called behavioral risk among principal construction participants. Behavior is affected by various risk factors; successful implementation of construction projects depends on effective management of the key risk factors. This paper identifies and ranks the critical behavioral risk factors from the perspective of principal construction participants in the Chinese construction industry. The data used for analysis is based on an interview and questionnaire survey. Factor analysis is conducted with the assistance of SPSS17.0. Forty-one potential behavioral risk factors are identified, with 30 of those being critical, including “client changes project objective or investment direction”, “designer uses technological capability advantage to obtain profit”, and others. These findings contribute to the understanding of risk management in the construction industry in China. They also serve as a useful reference for further studies on the subject.

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Section: Behavioral Risk In the Construction Industrymentioning

confidence: 99%

Critical Behavioral Risk Factors among Principal Participants in the Chinese Construction Industry

Pan

Jia

2018

Sustainability

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“…In recent years, association rules have also been employed in various fields of the building industry, e.g. occupational injuries in the building industry (Liao, Perng 2008), building project disputes (Chou et al 2016), building energy operational performance (Xiao, Fan 2014), and occupational accidents in construction sites (Cheng et al 2010;Amiri et al 2016;Li et al 2017).…”

Section: Data Miningmentioning

confidence: 99%

Examining Association Between Construction Inspection Grades and Critical Defects Using Data Mining and Fuzzy Logic

Lin

Fan²

2018

Journal of Civil Engineering and Management

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This paper explores the relations between defect types and quality inspection grades of public construction projects in Taiwan. Altogether, 499 defect types (classified from 17,648 defects) were found after analyzing 990 construction projects from the Public Construction Management Information System of the public construction commission which is a government unit that administers all the public construction. The core of this research includes the following steps. (1) Data mining (DM) was used to derive 57 association rules which altogether contain 30 of the 499 defect types. (2) K-means clustering was used to regroup the 990 projects of two attributes (defect frequency and original grading score of each project) into four new quality classes, so the 990 projects can be more evenly distributed in the four new classes and the correctness and reliability of the following analyses can be ensured. (3) Finally analysis of variance (ANOVA), fuzzy logic, and correlation analysis were used to verify that the aforementioned 30 defect types are the important ones determining inspection grades. Results of this research can help stakeholders of construction projects paying more attention on the root causes of the critical defect types so to dramatically raise their management effectiveness.

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“…It can be seen that safety incidents in the construction industry are still frequent and notorious and need to be addressed urgently. Accident investigations have demonstrated that construction workers' unsafe behaviors are the primary and main cause of accidents [7,8]. Heninrich et al [9] proposed that among 75,000 accidents cases, 88% of all industry accidents were caused by human errors.…”

Section: Introductionmentioning

confidence: 99%

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

Yue

Yang

et al. 2020

IJERPH

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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.

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Investigation of the causality patterns of non-helmet use behavior of construction workers

Cited by 62 publications

References 33 publications

Critical Behavioral Risk Factors among Principal Participants in the Chinese Construction Industry

Critical Behavioral Risk Factors among Principal Participants in the Chinese Construction Industry

Examining Association Between Construction Inspection Grades and Critical Defects Using Data Mining and Fuzzy Logic

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

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