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|Title:||Understanding and controlling the non-helmet use behavior of construction workers : an empirical and simulation study||Authors:||Li, Xiaoying||Advisors:||Li, Heng (BRE)||Keywords:||Construction workers
Construction industry -- Management
Construction industry -- Safety measures
Building -- Safety measures
|Issue Date:||2018||Publisher:||The Hong Kong Polytechnic University||Abstract:||The construction industry is regarded as one of the most hazardous and dangerous industries, with one of the highest accident rates. Head traumas are a common serious injury on construction sites and have attracted extensive attention from society. The cause of these injuries is often due to not wearing a safety helmet but the reasons for such unsafe behavior is not yet well understood. Despite the great importance of helmet use, data collection of helmet use and management methods on reducing non-helmet use behavior on construction sites is still in a relatively early stage. In order to provide valuable learning opportunities for the development of safety performance, therefore, this study aims to understand the root cause of non-helmet use behavior of construction workers from both individual and management levels, and explore how different supervision methods and punishment mechanisms could help to control the unsafe behavior. To achieve these aims, specifically, non-helmet use data was collected and analyzed by a real-time tracking system (Eye on Project) to investigate: (1) the impact of individual factors on non-helmet use behavior; (2) the impact of safety climate and productivity pressure on non-helmet use behavior; and (3) the impact of punishment systems and supervision methods on workers' behavioral patterns.
In order to gain a better understanding of how different types of factors influence non-helmet use behavior, this study has used three main analysis methods to achieve the research objectives: an association rule, system dynamics (SD) and an agent-based modeling system. Several findings were demonstrated by the empirical and simulation analyses: (1) The relationship between the non-helmet use behavior and individual's characteristics have been identified through an association-rule based approach, and the findings could help to establish a risk assessment matrix and advise construction managers or workers with the purpose of preventing the causality patterns. (2) Taking into consideration the impact of safety climate and productivity pressure, the proposed SD model works by understanding the feedback mechanisms involved in non-helmet use behavior when positive action is taken (i.e., safety training, communication and inspection) and the negative components of workplace stress on the safety climate of construction sites. (3) A better understanding of the effectiveness of multiple supervision methods and punishment amounts on non-helmet use behavior has been achieved based on the agent-based modeling method, and both punishments and supervision act as an effective role in reducing unsafe behavior and can be used as a management tool in practice; However, the negative influences of excessive punishment and supervision should be seriously considered and then prevented. Through investigating the relationship between contributory factors and non-helmet use behavior, and the impact of punishments and supervision methods, the findings not only provide an effective method for identifying factors related to unsafe behavior on construction sites but also help in developing more efficient and accurate risk assessment strategies. The proposed tool for objectively evaluating the number of individuals and periods of not using helmets on construction sites also overcomes the deficiencies of the traditional recording methods used in previous studies. The final analysis of empirical and simulation results can be used by project managers to implement safety management and stipulate safety rules on construction sites.
|Description:||89 pages : color illustrations
PolyU Library Call No.: [THS] LG51 .H577M BRE 2018 Li
|URI:||http://hdl.handle.net/10397/77356||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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Citations as of Dec 3, 2018
Citations as of Dec 3, 2018
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