Risk evaluation method and application of house building construction based on the multi-factor coupling effect

To accurately reflect the risk level of the housing building construction process and propose a new risk evaluation method. Firstly, grounded theory is used to conduct three-level coding on accident investigation reports to extract risk factors of housing building construction accidents. Secondly, combined with the coupling theory and the oscillator principle in physics, the coupling model of risk factors for housing building construction accidents is constructed to reveal the coupling mechanism of risk factors during accident occurrence. Then, according to the risk generation stage and relevant national standards and documents, the risk types and risk levels are divided. Finally, incorporating indicators such as coupling degree, proportion coefficient of abnormal factors, and inherent danger to personnel, the risk evaluation method of house building construction based on the multi-factor coupling effect (MFC) is proposed (including inherent risk evaluation and dynamic risk evaluation) and applied in the field. The results indicate that the MFC method improves the safety risk identification rate and assigns relatively higher risk levels to some risk events during the construction process, which has important practical significance for improving the safety management level of construction sites.

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Publication Details

Journal
International Journal of Construction Management
Published
2026-07-25
DOI
https://doi.org/10.1080/15623599.2026.2702378
Primary Topic
Construction Engineering and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

Risk evaluation method and application of house building construction based on the multi-factor coupling effect

Huina Ren, Lianhua Cheng, Dongqiang Cao, Huimin Guo et al.
International Journal of Construction Management
Construction Engineering and Safety
article

Risk evaluation method and application of house building construction based on the multi-factor coupling effect

Huina Ren, Lianhua Cheng, Dongqiang Cao, Huimin Guo, Xin Li
article en

Abstract

To accurately reflect the risk level of the housing building construction process and propose a new risk evaluation method. Firstly, grounded theory is used to conduct three-level coding on accident investigation reports to extract risk factors of housing building construction accidents. Secondly, combined with the coupling theory and the oscillator principle in physics, the coupling model of risk factors for housing building construction accidents is constructed to reveal the coupling mechanism of risk factors during accident occurrence. Then, according to the risk generation stage and relevant national standards and documents, the risk types and risk levels are divided. Finally, incorporating indicators such as coupling degree, proportion coefficient of abnormal factors, and inherent danger to personnel, the risk evaluation method of house building construction based on the multi-factor coupling effect (MFC) is proposed (including inherent risk evaluation and dynamic risk evaluation) and applied in the field. The results indicate that the MFC method improves the safety risk identification rate and assigns relatively higher risk levels to some risk events during the construction process, which has important practical significance for improving the safety management level of construction sites.

International Journal of Construction Management
Xi'an University of Science and Technology (CN), Metallurgical Corporation of China (China) (CN), Inner Mongolia University of Science and Technology (CN), Inner Mongolia University of Technology (CN)
Natural Science Basic Research Program of Shaanxi Province
Sustainable cities and communities
Openalex Percentile: Top 13%
Construction Engineering and Safety
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Risk evaluation method and application of house building construction based on the multi-factor coupling effect — Huina Ren, Lianhua Cheng, et al. · International Journal of Construction Management (2026) | TGRS Research Map | TGRS