Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/136792
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dc.contributor.authorZhang, Guizhenen_US
dc.contributor.authorThai, Vinh V.en_US
dc.contributor.authorLaw, Adrian Wing-Keungen_US
dc.contributor.authorYuen, Kum Faien_US
dc.contributor.authorLoh, Hui Shanen_US
dc.contributor.authorZhou, Qingjien_US
dc.date.accessioned2020-01-29T01:17:47Z-
dc.date.available2020-01-29T01:17:47Z-
dc.date.issued2019-
dc.identifier.citationZhang, G., Thai, V. V., Law, A. W.-K., Yuen, K. F., Loh, H. S., & Zhou, Q. (2019). Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling. Risk Analysis, 40(1), 8-23. doi:10.1111/risa.13374en_US
dc.identifier.issn0272-4332en_US
dc.identifier.urihttps://hdl.handle.net/10356/136792-
dc.description.abstractReducing the incidence of seafarers’ workplace injuries is of great importance to shipping and ship management companies. The objective of this study is to identify the important influencing factors and to build a quantitative model for the injury risk analysis aboard ships, so as to provide a decision support framework for effective injury prevention and management. Most of the previous research on seafarers’ occupational accidents either adopts a qualitative approach or applies simple descriptive statistics for analyses. In this study, the advanced method of a Bayesian network (BN) is used for the predictive modeling of seafarer injuries for its interpretative power as well as predictive capacity. The modeling is data driven and based on an extensive empirical survey to collect data on seafarers’ working practice and their injury records during the latest tour of duty, which could overcome the limitation of historical injury databases that mostly contain only data about the injured group instead of the entire population. Using the survey data, a BN model was developed consisting of nine major variables, including “PPE availability,” “Age,” and “Experience” of the seafarers, which were identified to be the most influential risk factors. The model was validated further with several tests through sensitivity analyses and logical axiom test. Finally, implementation of the result toward decision support for safety management in the global shipping industry was discussed.en_US
dc.language.isoenen_US
dc.relation.ispartofRisk Analysisen_US
dc.rights© 2019 Society for Risk Analysis. All rights reserved.en_US
dc.subjectEngineering::Civil engineeringen_US
dc.subjectEmpirical Surveysen_US
dc.subjectBayesian Networken_US
dc.titleQuantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modelingen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.contributor.schoolInterdisciplinary Graduate School (IGS)en_US
dc.contributor.researchNanyang Environment and Water Research Instituteen_US
dc.identifier.doi10.1111/risa.13374-
dc.identifier.issue1en_US
dc.identifier.volume40en_US
dc.identifier.spage8en_US
dc.identifier.epage23en_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
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