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Identifying key factors affecting the performance of team decision-making based on the analysis of investigation reports issued from diverse industries

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  • Ham, Dong-Han
  • Jung, Won-Jun
  • Park, Jinkyun

Abstract

Operational experience of sociotechnical systems has revealed that the degradation of their safety is attributable to human error. Accordingly, various kinds of human reliability analysis (HRA) techniques have been proposed over the past several decades for safety enhancement. The Fukushima accident, however, stressed that existing HRA techniques have a limitation in estimating the human error probability (HEP) of safety critical tasks that should be conducted under challenging circumstances (e.g., insufficient or misleading information) originating from the characteristics of a severe accident condition. This means that the very first step to properly estimate HEPs in severe accident conditions is to identify a catalog of key factors related to the performance of team decision-making tasks. This study therefore suggests a conceptual model based on significant factors pertaining to the performance of team decision-making tasks. Event investigation reports issued from diverse sociotechnical systems were analyzed along the proposed model, and as a result, 14 key factors were identified that could be a good starting point to scrutinize the performance of team decision-making tasks.

Suggested Citation

  • Ham, Dong-Han & Jung, Won-Jun & Park, Jinkyun, 2021. "Identifying key factors affecting the performance of team decision-making based on the analysis of investigation reports issued from diverse industries," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:reensy:v:206:y:2021:i:c:s0951832020308000
    DOI: 10.1016/j.ress.2020.107304
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    References listed on IDEAS

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    1. Ham, Dong-Han & Park, Jinkyun & Jung, Wondea, 2012. "Model-based identification and use of task complexity factors of human integrated systems," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 33-47.
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    Cited by:

    1. Lai, Hsueh-Yi, 2023. "Breakdowns in team resilience during aircraft landing due to mental model disconnects as identified through machine learning," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Rose, Rodrigo L. & Mugi, Sohan R. & Saleh, Joseph Homer, 2023. "Accident investigation and lessons not learned: AcciMap analysis of successive tailings dam collapses in Brazil," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    3. Asadayoobi, N. & Taghipour, S. & Jaber, M.Y., 2022. "Predicting human reliability based on probabilistic mission completion time using Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    4. Zhou, Jian-Lan & Yu, Ze-Tai & Xiao, Ren-Bin, 2022. "A large-scale group Success Likelihood Index Method to estimate human error probabilities in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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