Different uncertain factors obstruct the analysis of operational risks in container shipping, especially those rooted in the subjectivity of multiple risk assessments and their aggregation. This paper proposes a risk analysis model featuring a quantification of the uncertainty. Bayesian probability theory is employed to quantify the risk magnitude, while a dedicated module to handle uncertainty is enabled by Evidential Reasoning and a set of three uncertainty indicators, including expert ignorance, disagreement among experts, and polarization of their assessments. The situation of risk is diagnosed by risk ranking and visualized by risk mapping, using both Risk Magnitude Index and Uncertainty Index. The functionality of the proposed model in identifying critical and uncertain risks was demonstrated in an organizational-scale case study, followed by an examination of validity criteria and a sensitivity test. The case study reveals the physical flow as the dominant origin of high-ranking risks with potential significant consequences such as piracy, dangerous cargoes, and maritime accidents; while information and financial operational risks are more uncertain, especially cargo misdeclaration and unexpected rises of fuel costs.
History
Publication title
Reliability Engineering and System Safety
Volume
209
Article number
107362
Number
107362
ISSN
0951-8320
Department/School
Australian Maritime College
Publisher
Elsevier Sci Ltd
Place of publication
The Boulevard, Langford Lane, Kidlington, Oxford, England, Oxon, Ox5 1Gb
Rights statement
Copyright 2021 Elsevier
Repository Status
Restricted
Socio-economic Objectives
International sea freight transport (excl. live animals, food products and liquefied gas)