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Systematic review of human and organizational risks for probabilistic risk analysis in high-rise buildings

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  • Tan, Samson
  • Moinuddin, Khalid

Abstract

For fire risk experts, the most parsimonious model is one that identifies errors due to human and organizational factors (HOFs) that can be changed through a series of interventions. This is a difficult task because of the dearth of studies to identify these types of events. However, it is possible to examine and identify human and organizational errors (HOEs) within fire risk situations. Many errors identified in fire risk environments are due to human factors that can be changed through employee training and development. In addition, many organizational factors, such as safety culture, can be changed over time through transformational interventions that shift existing mindsets. This paper presents a systematic review to identify errors due to human and organizational factors that apply to and potentially affect risk estimates in fire safety modelling of high-rise buildings. First, the paper describes the types of errors that occur in fire risk situations and then provides a review that categorizes and links human and organizational factors. The paper is both a qualitative and quantitative review, drawing on research from quantitative studies and case studies, including the Grenfell Fire. The review offers insights and recommendations to incorporate human and organizational risks into probabilistic risk analyses and suggests future directions for research.

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  • Tan, Samson & Moinuddin, Khalid, 2019. "Systematic review of human and organizational risks for probabilistic risk analysis in high-rise buildings," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 233-250.
    • Handle: RePEc:eee:reensy:v:188:y:2019:i:c:p:233-250
    DOI: 10.1016/j.ress.2019.03.012
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    3. Wang, Ning & Xu, Yan & Wang, Sutong, 2022. "Interpretable boosting tree ensemble method for multisource building fire loss prediction," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    4. Takeda, Satoshi & Kitada, Takanori, 2021. "Simple method based on sensitivity coefficient for stochastic uncertainty analysis in probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    5. Junlong Peng & Chao Peng & Mengyao Wang & Ke Hu & Dubin Wu, 2022. "Research on the factors of extremely short construction period under the sufficient resources based on Grey-DEMATEL-ISM," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-21, March.
    6. Liu, Zengkai & Ma, Qiang & Cai, Baoping & Shi, Xuewei & Zheng, Chao & Liu, Yonghong, 2022. "Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).

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