Modification of HFACS model for path identification of causal factors of collapse accidents in the construction industry

鉴定(生物学) 工程类 岩土工程 法律工程学 地质学 生物 植物
作者
Haonan Qi,Zhipeng Zhou,Javier Irizarry,Xiaopeng Deng,Y. F. Yang,Nan Li,Jianliang Zhou
出处
期刊:Engineering, Construction and Architectural Management [Emerald Publishing Limited]
卷期号:32 (7): 4718-4745 被引量:31
标识
DOI:10.1108/ecam-02-2023-0101
摘要

Purpose This study aims to modify the human factors analysis and classification system (HFACS) to make it suitable for collapse accident analysis in construction. Based upon the modified HFACS, distribution patterns of causal factors across multiple levels were discerned among causal factors of various stakeholders at construction sites. It explored the correlations between two causal factors from different levels and further determined causation paths from two perspectives of level and stakeholder. Design/methodology/approach The main research framework consisted of data collection, coding and analysis. Collapse accident reports were collected with adequate causation information. The modified HFACS was utilized for coding causal factors across all five levels in each case. A hybrid approach with two perspectives of level and stakeholder was proposed for frequency analysis, correlation analysis and path identification between causal factors. Findings Eight causal factors from external organizations at the fifth level were added to the original HFACS. Level-based correlation analyses and path identification provided safety managers with a holistic view of inter-connected causal factors across five levels. Stakeholder-based correlation analyses between causal factors from the fifth level and its non-adjacent levels were implemented based on client, government and third parties. These identified paths were useful for different stakeholders to develop specific safety plans for avoiding construction collapse accidents. Originality/value This paper fulfils an identified need to modify and utilize the HFACS model for correlation analysis and path identification of causal factors resulting in collapse accidents, which can provide opportunities for tailoring preventive and protective measures at construction sites.
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