Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling
Reducing 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 decis...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/136792 |
| _version_ | 1826114205104734208 |
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| author | Zhang, Guizhen Thai, Vinh V. Law, Adrian Wing-Keung Yuen, Kum Fai Loh, Hui Shan Zhou, Qingji |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Zhang, Guizhen Thai, Vinh V. Law, Adrian Wing-Keung Yuen, Kum Fai Loh, Hui Shan Zhou, Qingji |
| author_sort | Zhang, Guizhen |
| collection | NTU |
| description | Reducing 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. |
| first_indexed | 2024-10-01T03:35:40Z |
| format | Journal Article |
| id | ntu-10356/136792 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:35:40Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1367922020-11-18T08:51:47Z Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling Zhang, Guizhen Thai, Vinh V. Law, Adrian Wing-Keung Yuen, Kum Fai Loh, Hui Shan Zhou, Qingji School of Civil and Environmental Engineering Interdisciplinary Graduate School (IGS) Nanyang Environment and Water Research Institute Engineering::Civil engineering Empirical Surveys Bayesian Network Reducing 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. 2020-01-29T01:17:47Z 2020-01-29T01:17:47Z 2019 Journal Article Zhang, 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.13374 0272-4332 https://hdl.handle.net/10356/136792 10.1111/risa.13374 1 40 8 23 en Risk Analysis © 2019 Society for Risk Analysis. All rights reserved. |
| spellingShingle | Engineering::Civil engineering Empirical Surveys Bayesian Network Zhang, Guizhen Thai, Vinh V. Law, Adrian Wing-Keung Yuen, Kum Fai Loh, Hui Shan Zhou, Qingji Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling |
| title | Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling |
| title_full | Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling |
| title_fullStr | Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling |
| title_full_unstemmed | Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling |
| title_short | Quantitative risk assessment of seafarers’ nonfatal injuries due to occupational accidents based on Bayesian network modeling |
| title_sort | quantitative risk assessment of seafarers nonfatal injuries due to occupational accidents based on bayesian network modeling |
| topic | Engineering::Civil engineering Empirical Surveys Bayesian Network |
| url | https://hdl.handle.net/10356/136792 |
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