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

Son Nguyen

Maritime Policy & Management, 2020, vol. 47, issue 6, 778-796

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.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/03088839.2020.1729432 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:marpmg:v:47:y:2020:i:6:p:778-796

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TMPM20

DOI: 10.1080/03088839.2020.1729432

Access Statistics for this article

Maritime Policy & Management is currently edited by Dr Kevin Li and Heather Leggate McLaughlin

More articles in Maritime Policy & Management from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().