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.
Acknowledgments
The article has been partially supported by the Tasmania Graduate Research Scholarship. The authors are grateful to the Associate Editor and anonymous reviewers for their useful comments and suggestions to the earlier versions of this paper. The authors also appreciate the valuable contribution of the participated experts from the shipping company in the case study.
Disclosure statement
No potential conflict of interest was reported by the author.
Correction Statement
This article has been republished with minor changes. These changes do not impact the academic content of the article.