期刊
RISK ANALYSIS
卷 40, 期 1, 页码 8-23出版社
WILEY
DOI: 10.1111/risa.13374
关键词
Bayesian network; empirical surveys; risk prediction; seafarer; workplace injury
类别
资金
- Interdisciplinary Graduate School of Nanyang Technological University (NTU)
- DHI-NTU (Danish Hydraulic Institute-Nanyang Technological University) Centre, under the umbrella of Nanyang Environment and Water Research Institute of NTU
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据