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A risk assessment model with systematical uncertainty treatment for container shipping operations

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  • Son Nguyen

Abstract

The substantial adverse effects of risk factors on container shipping and logistics promoted a deep integration of risk analysis into the decision-making process. This paper aims to develop a well-grounded quantitative model to operational risk in a container shipping context. Considering uncertainty as a primary component of the risk concept, methods were employed in an inter-complementary manner to enable not only a sense of foreseeability but also a deeper look into the weaknesses of the knowledge base. The intersubjectivity of the input extraction process was supported by the Evidential Reasoning (ER) algorithm. Risks are then assessed based on a Fuzzy Rules Bayesian Network (FRBN) model with a 2-level parameter structure before meaningful interpretations can be derived through a new risk mapping approach. Besides an illustrative case study, the model was tested by sensitivity analysis and an examination of multiple validity claims.

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  • Son Nguyen, 2020. "A risk assessment model with systematical uncertainty treatment for container shipping operations," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(6), pages 778-796, August.
    • Handle: RePEc:taf:marpmg:v:47:y:2020:i:6:p:778-796
    DOI: 10.1080/03088839.2020.1729432
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    Cited by:

    1. Nguyen, Son & Chen, Peggy Shu-Ling & Du, Yuquan & Thai, Vinh V., 2021. "An Operational Risk Analysis Model for Container Shipping Systems considering Uncertainty Quantification," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Hristos Karahalios, 2021. "Contribution of PSC Authorities to Ship Accident Prevention," SN Operations Research Forum, Springer, vol. 2(1), pages 1-18, March.
    3. Zhou, Yusheng & Li, Xue & Yuen, Kum Fai, 2022. "Holistic risk assessment of container shipping service based on Bayesian Network Modelling," Reliability Engineering and System Safety, Elsevier, vol. 220(C).

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