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Assessing offshore emergency evacuation behavior in a virtual environment using a Bayesian Network approach

Author

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  • Musharraf, Mashrura
  • Smith, Jennifer
  • Khan, Faisal
  • Veitch, Brian
  • MacKinnon, Scott

Abstract

In the performance influencing factor (PIF) hierarchy, person-based influencing factors reside in the top level along with machine-based, team-based, organization-based and situation/stressor-based factors. Though person-based PIFs like morale, motivation, and attitude (MMA) play an important role in shaping performance, it is nearly impossible to assess such PIFs directly. However, it is possible to measure behavioral indicators (e.g. compliance, use of information) that can provide insight regarding the state of the unobservable person-based PIFs. One common approach to measuring these indicators is to carry out a self-reported questionnaire survey. Significant work has been done to make such questionnaires reliable, but the potential validity problem associated with any questionnaire is that the data are subjective and thus may bear a limited relationship to reality. This paper describes the use of a virtual environment to measure behavioral indicators, which in turn can be used as proxies to assess otherwise unobservable PIFs like MMA. A Bayesian Network (BN) model is first developed to define the relationship between person-based PIFs and measurable behavioral indicators. The paper then shows how these indicators can be measured using evidence collected from a virtual environment of an offshore petroleum installation. A study that focused on emergency evacuation scenarios was done with 36 participants. The participants were first assessed using a multiple choice test. They were then assessed based on their observed performance during simulated offshore emergency evacuation conditions. A comparison of the two assessments demonstrates the potential benefits and challenges of using virtual environments to assess behavioral indicators, and thus the person-based PIFs.

Suggested Citation

  • Musharraf, Mashrura & Smith, Jennifer & Khan, Faisal & Veitch, Brian & MacKinnon, Scott, 2016. "Assessing offshore emergency evacuation behavior in a virtual environment using a Bayesian Network approach," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 28-37.
  • Handle: RePEc:eee:reensy:v:152:y:2016:i:c:p:28-37
    DOI: 10.1016/j.ress.2016.02.001
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Monferini, A. & Konstandinidou, M. & Nivolianitou, Z. & Weber, S. & Kontogiannis, T. & Kafka, P. & Kay, A.M. & Leva, M.C. & Demichela, M., 2013. "A compound methodology to assess the impact of human and organizational factors impact on the risk level of hazardous industrial plants," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 280-289.
    3. Groth, Katrina M. & Mosleh, Ali, 2012. "A data-informed PIF hierarchy for model-based Human Reliability Analysis," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 154-174.
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    Cited by:

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    13. Shirley, Rachel Benish & Smidts, Carol & Zhao, Yunfei, 2020. "Development of a quantitative Bayesian network mapping objective factors to subjective performance shaping factor evaluations: An example using student operators in a digital nuclear power plant simul," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    14. Musharraf, Mashrura & Smith, Jennifer & Khan, Faisal & Veitch, Brian, 2020. "Identifying route selection strategies in offshore emergency situations using decision trees," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    15. Cheng, Tingting & Veitch, Erik A. & Utne, Ingrid Bouwer & Ramos, Marilia A. & Mosleh, Ali & Alsos, Ole Andreas & Wu, Bing, 2024. "Analysis of human errors in human-autonomy collaboration in autonomous ships operations through shore control experimental data," Reliability Engineering and System Safety, Elsevier, vol. 246(C).

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