Zhengkai Zhao , Shu Zhang , Xinyu Hua , Xiuzhi Shi
{"title":"Investigating construction workers' perception of risk, likelihood, and severity using electroencephalogram and machine learning","authors":"Zhengkai Zhao , Shu Zhang , Xinyu Hua , Xiuzhi Shi","doi":"10.1016/j.autcon.2024.105814","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding how workers perceive risk is essential to construction safety management. Firstly, an event-related potential (ERP) experiment was conducted to investigate the relationship between risk, likelihood, and severity. Then, a linear model was developed to predict workers' risk perception based on ERP components and quantify the relative importance of severity to likelihood. Finally, an additive model was constructed to reflect the risk perception pattern. The results indicate: (1) Workers' emotional responses stem from the process of associating accident consequences in severity assessment, which is represented by the late positive potential (LPP) component. (2) Workers' risk perception relies more on severity compared with likelihood. (3) The additive model (risk = 0.203 * likelihood +0.758 * severity) better matches the risk perception patterns than the multiplicative model. The research results provide a new perspective for understanding workers' risk perception patterns and contributing to proactive safety management in the construction industry.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6000,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation in Construction","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926580524005508","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding how workers perceive risk is essential to construction safety management. Firstly, an event-related potential (ERP) experiment was conducted to investigate the relationship between risk, likelihood, and severity. Then, a linear model was developed to predict workers' risk perception based on ERP components and quantify the relative importance of severity to likelihood. Finally, an additive model was constructed to reflect the risk perception pattern. The results indicate: (1) Workers' emotional responses stem from the process of associating accident consequences in severity assessment, which is represented by the late positive potential (LPP) component. (2) Workers' risk perception relies more on severity compared with likelihood. (3) The additive model (risk = 0.203 * likelihood +0.758 * severity) better matches the risk perception patterns than the multiplicative model. The research results provide a new perspective for understanding workers' risk perception patterns and contributing to proactive safety management in the construction industry.
期刊介绍:
Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities.
The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.