4.7 Review

Review of techniques and challenges of human and organizational factors analysis in maritime transportation

期刊

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2021.108249

关键词

Human and organizational factors; Maritime transportation; Identification techniques; Human error probability quantification; Challenges for future

资金

  1. International Cooperation and Exchange of the National Natural Science Foundation of China [51920105014]
  2. National Natural Science Foundation of China [52071248, 51809206]
  3. Hubei Natural Science Foundation [2021CFB312]
  4. Fundamental Research Funds for the Central Universities [WUT:2020III041, WUT:2021IVB066]
  5. Portuguese Foundation for Science and Technology (Fundacao para a Ciencia e Tecnologia - FCT) [UIDB/UIDP/00134/2020]

向作者/读者索取更多资源

This paper summarises the advanced techniques for analysing human and organizational factors in maritime accidents, as well as the attempts to reduce human errors by identifying the existing challenges. The most widely used modelling techniques for human error identification and probability quantification are discussed. The paper also highlights the challenges for future studies, such as data collection, individual factors, and autonomous shipping. Overall, this paper provides valuable insight into human and organizational factors in maritime transportation.
This paper summarises the advanced techniques adopted for the analysis of human and organizational factors, which are the predominant factors in maritime accidents, and the various attempts that have been made to reduce human errors by identifying the existing challenges. Advanced techniques for human and organizational factor modelling, including human error identification in accident investigation, human error probability quantification in risk analysis, and human and organizational factor analysis for emergency situations, are comprehensively analysed and discussed. The most widely used modelling technique for human error identification is the Human Factors Analysis and Classification System (HFACS), and preconditions and unsafe acts exert the most important impacts on maritime accidents in previous studies. Moreover, Cognitive Reliability Error Analysis (CREAM) is the most widely used technique for human error probability quantification, and fuzzy, evidential reasoning and Bayesian networks are often incorporated for common performance condition (CPC) quantification and synthesis processes. In the future, other techniques should be introduced and developed for modelling HOFs for maritime transportation. Moreover, the challenges for human and organizational factors, including data collection, individual factors, and autonomous shipping, are identified for future studies. Consequently, this paper provides insight into human and organizational factors for maritime transportation, including quantification modelling, solutions to data collection and future research directions.

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