Jiangshi Zhang1, Wenyue Zhang2, Peihui Xu2, Na Chen3. 1. School of Resources and Safety Engineering, China University of Mining and Technology, D11, Xueyuan Road, Haidian District, Beijing 100083, China. Electronic address: zjsh0426@163.com. 2. School of Resources and Safety Engineering, China University of Mining and Technology, D11, Xueyuan Road, Haidian District, Beijing 100083, China. 3. School of Mechanics and Engineering Science, Zhengzhou University, Zhengzhou 450001, 100 Science Avenue, Zhengzhou City, China. Electronic address: nchen@zzu.edu.cn.
Abstract
INTRODUCTION: It is necessary to clearly understand construction accidents for preventing a rise in Chinese construction accidents and deaths. Better analysis methods are required for Chinese construction sector accidents. METHODS: Choosing and analyzing a typical construction accident based on four popular contemporary accident causation models: STAMP, AcciMap, HFACS, and the 2-4 Model. Then we evaluated the models' applicability to construction accidents, including their usability, reliability, and validity. RESULTS: STAMP addressed how complexity within the accident system influenced the accident development, and its output makes the responsibilities clearer for the accident. AcciMap described the entire system's failure, the entire accident's trajectory, and the relationship between them. AcciMap showed that the accident was a dynamic developing process, and this method has a high usability. The taxonomic nature of HFACS is an important feature that provides it with a high reliability. In the accident reviewed here, we found that poor management was a critical factor rather than the individual factor in the accident. The 2-4 Model provided detailed causes of the accident and established the relationship among the accident causes, the safety management system, and the safety culture. It also avoided capturing all of the complexity in the large sociotechnical system and revealed a dynamic analysis and developing process. We confirmed that it has a high usability and validity. Therefore, the 2-4Model is recommended for future Chinese construction accident analysis efforts. PRACTICAL APPLICATIONS: The study provides a useful, reliable, and effective analysis method for Chinese construction accidents.
INTRODUCTION: It is necessary to clearly understand construction accidents for preventing a rise in Chinese construction accidents and deaths. Better analysis methods are required for Chinese construction sector accidents. METHODS: Choosing and analyzing a typical construction accident based on four popular contemporary accident causation models: STAMP, AcciMap, HFACS, and the 2-4 Model. Then we evaluated the models' applicability to construction accidents, including their usability, reliability, and validity. RESULTS: STAMP addressed how complexity within the accident system influenced the accident development, and its output makes the responsibilities clearer for the accident. AcciMap described the entire system's failure, the entire accident's trajectory, and the relationship between them. AcciMap showed that the accident was a dynamic developing process, and this method has a high usability. The taxonomic nature of HFACS is an important feature that provides it with a high reliability. In the accident reviewed here, we found that poor management was a critical factor rather than the individual factor in the accident. The 2-4 Model provided detailed causes of the accident and established the relationship among the accident causes, the safety management system, and the safety culture. It also avoided capturing all of the complexity in the large sociotechnical system and revealed a dynamic analysis and developing process. We confirmed that it has a high usability and validity. Therefore, the 2-4Model is recommended for future Chinese construction accident analysis efforts. PRACTICAL APPLICATIONS: The study provides a useful, reliable, and effective analysis method for Chinese construction accidents.
Authors: Yukyung Shim; Jaemin Jeong; Jaewook Jeong; Jaehyun Lee; Yongwoo Kim Journal: Int J Environ Res Public Health Date: 2022-02-17 Impact factor: 3.390
Authors: Lin Liu; Qiang Mei; Lixin Jiang; Jinnan Wu; Suxia Liu; Meng Wang Journal: Int J Environ Res Public Health Date: 2021-03-08 Impact factor: 3.390