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.

Item Type:	Refereed Article
Keywords:	risk assessment; container shipping operation;Bayesian network; evidential reasoning; risk mapping
Research Division:	Commerce, Management, Tourism and Services
Research Group:	Transportation, logistics and supply chains
Research Field:	Maritime transportation and freight services
Objective Division:	Transport
Objective Group:	Water transport
Objective Field:	International sea freight transport (excl. live animals, food products and liquefied gas)
UTAS Author:	Nguyen, S (Mr Son Nguyen)
ID Code:	150561
Year Published:	2020
Web of Science® Times Cited:	8
Deposited By:	Maritime and Logistics Management
Deposited On:	2022-06-20
Last Modified:	2022-09-28
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