Analysis of HFE impact of COVID-19 on OHS in construction enterprises
Human factors are critical to Occupational Health and Safety (OHS) in construction enterprises. However, comprehensive industry-wide recognition remains challenging, underscoring the need for Human Factors Engineering (HFE) research. This study develops an optimized HFE evaluation model based on fun...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024173069 |
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| author | Zhonghong Cao Junjie Zhu Zhenzhen Wang |
| author_facet | Zhonghong Cao Junjie Zhu Zhenzhen Wang |
| author_sort | Zhonghong Cao |
| collection | DOAJ |
| description | Human factors are critical to Occupational Health and Safety (OHS) in construction enterprises. However, comprehensive industry-wide recognition remains challenging, underscoring the need for Human Factors Engineering (HFE) research. This study develops an optimized HFE evaluation model based on fundamental HFE principles. Examining COVID-19's significant impact on construction enterprise OHS, this research employs an empirical investigation of 259 cases, utilizing a model that integrates NetLogo's System Dynamics (SD) and Multiple Linear Regression (MLR) to analyze the interactions between human factors and other variables. The findings reveal four key factors influencing human factors: management, material, environmental, and methodological. These factors demonstrate a quadratic parabolic relationship, with peak influence occurring at step 36 of the research period. Twelve of the 20 survey factors exhibit a linear regression relationship with human factors' four sub-factors, with pre-job training (Q9) demonstrating multiple influential interactions. The strongest correlation is between pre-job training (Q9) and living materials (Q14), with a weight coefficient of .325. Psychological counseling (Q8) and living materials (Q14) show a close relationship (weight coefficient .301). Notably, Q9 and empirical prevention materials (Q11) display a negative correlation with a weight coefficient of −.156. This study's practical significance lies in enabling enterprises to identify key HFE control factors and understand critical sub-factors for mitigating COVID-19's adverse impacts. |
| format | Article |
| id | doaj-art-12a232f5788e4b0e86e609d12a4af948 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-12a232f5788e4b0e86e609d12a4af9482025-01-17T04:50:44ZengElsevierHeliyon2405-84402025-01-01111e41275Analysis of HFE impact of COVID-19 on OHS in construction enterprisesZhonghong Cao0Junjie Zhu1Zhenzhen Wang2School of Economics and Management, Hunan University of Science and Engineering, Yongzhou, 425199, Hunan, PR China; Corresponding author.School of accounting, Wuhan Qingchuan University, Wuhan, 430204, Hubei, PR ChinaSchool of accounting, Wuhan Qingchuan University, Wuhan, 430204, Hubei, PR ChinaHuman factors are critical to Occupational Health and Safety (OHS) in construction enterprises. However, comprehensive industry-wide recognition remains challenging, underscoring the need for Human Factors Engineering (HFE) research. This study develops an optimized HFE evaluation model based on fundamental HFE principles. Examining COVID-19's significant impact on construction enterprise OHS, this research employs an empirical investigation of 259 cases, utilizing a model that integrates NetLogo's System Dynamics (SD) and Multiple Linear Regression (MLR) to analyze the interactions between human factors and other variables. The findings reveal four key factors influencing human factors: management, material, environmental, and methodological. These factors demonstrate a quadratic parabolic relationship, with peak influence occurring at step 36 of the research period. Twelve of the 20 survey factors exhibit a linear regression relationship with human factors' four sub-factors, with pre-job training (Q9) demonstrating multiple influential interactions. The strongest correlation is between pre-job training (Q9) and living materials (Q14), with a weight coefficient of .325. Psychological counseling (Q8) and living materials (Q14) show a close relationship (weight coefficient .301). Notably, Q9 and empirical prevention materials (Q11) display a negative correlation with a weight coefficient of −.156. This study's practical significance lies in enabling enterprises to identify key HFE control factors and understand critical sub-factors for mitigating COVID-19's adverse impacts.http://www.sciencedirect.com/science/article/pii/S2405844024173069Occupational health and safety (OHS)COVID-19Human factors engineering (HFE)Multiple linear regression (MLR)NetLogoSystem dynamics (SD) |
| spellingShingle | Zhonghong Cao Junjie Zhu Zhenzhen Wang Analysis of HFE impact of COVID-19 on OHS in construction enterprises Heliyon Occupational health and safety (OHS) COVID-19 Human factors engineering (HFE) Multiple linear regression (MLR) NetLogo System dynamics (SD) |
| title | Analysis of HFE impact of COVID-19 on OHS in construction enterprises |
| title_full | Analysis of HFE impact of COVID-19 on OHS in construction enterprises |
| title_fullStr | Analysis of HFE impact of COVID-19 on OHS in construction enterprises |
| title_full_unstemmed | Analysis of HFE impact of COVID-19 on OHS in construction enterprises |
| title_short | Analysis of HFE impact of COVID-19 on OHS in construction enterprises |
| title_sort | analysis of hfe impact of covid 19 on ohs in construction enterprises |
| topic | Occupational health and safety (OHS) COVID-19 Human factors engineering (HFE) Multiple linear regression (MLR) NetLogo System dynamics (SD) |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024173069 |
| work_keys_str_mv | AT zhonghongcao analysisofhfeimpactofcovid19onohsinconstructionenterprises AT junjiezhu analysisofhfeimpactofcovid19onohsinconstructionenterprises AT zhenzhenwang analysisofhfeimpactofcovid19onohsinconstructionenterprises |