IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v188y2019icp233-250.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832018310111
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2019.03.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lin, P.H. & Hale, A.R. & van Gulijk, C., 2013. "A paired comparison approach to improve the quantification of management influences in air transportation," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 52-60.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Sakurahara, Tatsuya & Mohaghegh, Zahra & Reihani, Seyed & Kee, Ernie & Brandyberry, Mark & Rodgers, Shawn, 2018. "An integrated methodology for spatio-temporal incorporation of underlying failure mechanisms into fire probabilistic risk assessment of nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 242-257.
    4. Mohaghegh, Zahra & Kazemi, Reza & Mosleh, Ali, 2009. "Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 1000-1018.
    5. Maryam Tabibzadeh & Najmedin Meshkati, 2014. "Learning from the BP Deepwater Horizon accident: risk analysis of human and organizational factors in negative pressure test," Environment Systems and Decisions, Springer, vol. 34(2), pages 194-207, June.
    6. Wu, Chao & Huang, Lang, 2019. "A new accident causation model based on information flow and its application in Tianjin Port fire and explosion accident," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 73-85.
    7. Aven, Terje, 2008. "A semi-quantitative approach to risk analysis, as an alternative to QRAs," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 790-797.
    8. Coen van Gulijk & Peter Hughes & Miguel Figueres-Esteban & Rawia El-Rashidy & George Bearfield, 2018. "The case for IT transformation and big data for safety risk management on the GB railways," Journal of Risk and Reliability, , vol. 232(2), pages 151-163, April.
    9. Hanea, D.M. & Jagtman, H.M. & Ale, B.J.M., 2012. "Analysis of the Schiphol Cell Complex fire using a Bayesian belief net based model," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 115-124.
    10. Skogdalen, Jon Espen & Vinnem, Jan Erik, 2012. "Quantitative risk analysis of oil and gas drilling, using Deepwater Horizon as case study," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 58-66.
    11. Groth, Katrina M. & Swiler, Laura P., 2013. "Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 33-42.
    12. Michael K. Lindell & Ronald W. Perry, 2012. "The Protective Action Decision Model: Theoretical Modifications and Additional Evidence," Risk Analysis, John Wiley & Sons, vol. 32(4), pages 616-632, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alexis Cantizano & Raquel Caro & Mercedes Fernández & Pablo Ayala, 2022. "Human Factors in the Model of Urban Fire Spread in Madrid (Spain) Focused on the Poor Population," Sustainability, MDPI, vol. 14(8), pages 1-13, April.
    2. 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).
    3. 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).
    4. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    2. Kim, Yochan & Park, Jinkyun & Jung, Wondea, 2017. "A quantitative measure of fitness for duty and work processes for human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 595-601.
    3. Justin Pence & Zahra Mohaghegh, 2020. "A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1183-1211, June.
    4. Pence, Justin & Sakurahara, Tatsuya & Zhu, Xuefeng & Mohaghegh, Zahra & Ertem, Mehmet & Ostroff, Cheri & Kee, Ernie, 2019. "Data-theoretic methodology and computational platform to quantify organizational factors in socio-technical risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 240-260.
    5. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    6. Bui, Ha & Sakurahara, Tatsuya & Pence, Justin & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 405-428.
    7. Kenneth Pettersen Gould, 2021. "Organizational Risk: “Muddling Through” 40 Years of Research," Risk Analysis, John Wiley & Sons, vol. 41(3), pages 456-465, March.
    8. Christoph Alexander Thieme & Ingrid Bouwer Utne, 2017. "A risk model for autonomous marine systems and operation focusing on human–autonomy collaboration," Journal of Risk and Reliability, , vol. 231(4), pages 446-464, August.
    9. Maryam Tabibzadeh & Najmedin Meshkati, 2014. "Learning from the BP Deepwater Horizon accident: risk analysis of human and organizational factors in negative pressure test," Environment Systems and Decisions, Springer, vol. 34(2), pages 194-207, June.
    10. Aven, Terje & Zio, Enrico, 2011. "Some considerations on the treatment of uncertainties in risk assessment for practical decision making," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 64-74.
    11. Pence, Justin & Abolhelm, Marzieh & Mohaghegh, Zahra & Reihani, Seyed & Ertem, Mehmet & Kee, Ernie, 2018. "Methodology to evaluate the monetary benefit of Probabilistic Risk Assessment by modeling the net value of Risk-Informed Applications at nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 171-182.
    12. Bevilacqua, Maurizio & Ciarapica, Filippo Emanuele, 2018. "Human factor risk management in the process industry: A case study," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 149-159.
    13. Abrishami, Shokoufeh & Khakzad, Nima & Hosseini, Seyed Mahmoud, 2020. "A data-based comparison of BN-HRA models in assessing human error probability: An offshore evacuation case study," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    14. Seyed M. Miran & Chen Ling & Alan Gerard & Lans Rothfusz, 2019. "Effect of Providing the Uncertainty Information About a Tornado Occurrence on the Weather Recipients’ Cognition and Protective Action: Probabilistic Hazard Information Versus Deterministic Warnings," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1533-1545, July.
    15. Patriarca, Riccardo & Ramos, Marilia & Paltrinieri, Nicola & Massaiu, Salvatore & Costantino, Francesco & Di Gravio, Giulio & Boring, Ronald Laurids, 2020. "Human reliability analysis: Exploring the intellectual structure of a research field," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    16. Sakurahara, Tatsuya & Schumock, Grant & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "Simulation-Informed Probabilistic Methodology for Common Cause Failure Analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 84-99.
    17. Myriam Merad, 2014. "Expertise processes in risk assessment and management: How to improve their governance and their conduct?," Environment Systems and Decisions, Springer, vol. 34(2), pages 181-182, June.
    18. Liu, Peng & Qiu, Yongping & Hu, Juntao & Tong, Jiejuan & Zhao, Jun & Li, Zhizhong, 2020. "Expert judgments for performance shaping Factors’ multiplier design in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    19. Thomas J. Cova & Philip E. Dennison & Dapeng Li & Frank A. Drews & Laura K. Siebeneck & Michael K. Lindell, 2017. "Warning Triggers in Environmental Hazards: Who Should Be Warned to Do What and When?," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 601-611, April.
    20. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2016. "Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 93-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:188:y:2019:i:c:p:233-250. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.