4.7 Article

A methodology to assess the interrelationships between contributory factors to maritime transport accidents of dangerous goods in China

期刊

OCEAN ENGINEERING
卷 266, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2022.112769

关键词

Maritime accidents; Dangerous goods; Risk assessment; DEMATEL; Bayesian network

资金

  1. National Key Research and Development Program of China
  2. Dalian Science and Technology Bureau
  3. Social Science Planning Fund of Liaoning Province
  4. Fundamental Research Funds for the Central Universities
  5. [2019YFB1600601]
  6. [2021RD09]
  7. [L22CGL004]
  8. [3132022343]
  9. [2022HDZKB14]

向作者/读者索取更多资源

A comprehensive risk analysis methodology is proposed to evaluate the contributory factors and their hierarchical interrelationships involved in maritime transport accidents of dangerous goods. The methodology integrates the advantages of DEMATEL, ISM, and FBN, and provides more detailed quantitative assessment of risk factors contributing to maritime transport accidents.
A comprehensive risk analysis methodology is proposed in the present study to evaluate the contributory factors and their hierarchical interrelationships involved in maritime transport accidents of dangerous goods (DG). The methodology integrates the advantages of decision making trial and evaluation laboratory (DEMATEL), inter-pretive structure modelling (ISM) and fuzzy Bayesian network (FBN). First, 20 contributing factors are identified based on reports of 22 accidents in China, expert knowledge and literature review. DEMATEL is then utilized to visual the cause-effect relationships of contributing factors; ISM is adopted to build a hierarchical structure of contributing factors; by mapping the hierarchical structure and employing fuzzy sets to collect expert judge-ments, a BN model is established in the end. The results show that a more detailed quantitative assessment of risk factors contributing to maritime transport accidents of DG can be provided by applying the proposed method-ology, including the influencing degree, influenced degree, centrality, causality, hierarchical relation, sensitivity degree, and important-sensitivity matrix, etc., which are unavailable in traditional risk analysis approaches.

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