Bayesian Network Analysis of Industrial Accident Risk for Fishers on Fishing Vessels Less Than 12 m in Length

被引:1
作者
Lee, Seung-Hyun [1 ]
Kim, Su-Hyung [1 ]
Ryu, Kyung-Jin [2 ]
Lee, Yoo-Won [2 ]
机构
[1] Pukyong Natl Univ, Training Ship, Busan 48513, South Korea
[2] Pukyong Natl Univ, Div Marine Prod Syst Management, Busan 48513, South Korea
关键词
Bayesian network analysis; fishing vessel; industrial accident; Formal Safety Assessment; EXPERT ELICITATION; MODEL;
D O I
10.3390/su16103977
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Marine Stewardship Council estimates that approximately 38 million people worldwide work in fisheries, and more than one-third of the global population is dependent on aquatic products for protein, highlighting the importance of sustainable fisheries. The FISH Safety Foundation reports that 300 fishers die every day. To achieve sustainable fisheries as a primary industry, the safety of human resources is of the utmost importance. The International Maritime Organization (IMO) and the International Labor Organization (ILO) have made efforts towards this goal, including the issuance of agreements and guidelines to reduce industrial accidents among fishing vessel workers. The criterion for applying these guidelines is usually a total ship length >= 12 m or >= 24 m. However, a vast majority of registered fishing vessels are <12 m long, and the fishers of these vessels suffer substantially more industrial accidents. Thus, we conducted a quantitative analysis of 1093 industrial accidents affecting fishers on fishing vessels <12 m in length, analyzed risk using a Bayesian network analysis (a method proposed by the Formal Safety Assessment of the IMO), and administered a questionnaire survey to a panel of experts in order to ascertain the risk for different types of industrial accidents and propose specific measures to reduce this risk.
引用
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页数:21
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