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Impacts of dynamic inspection records on port state control efficiency using Bayesian network analysis

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  • Fan, Lixian
  • Zhang, Meng
  • Yin, Jingbo
  • Zhang, Jinfen

Abstract

The risk level of shipping transportation is important as it will cause enormous losses once an accident occurs. This study focuses on the effect of Port State Control as which is gradually becoming an important defence for maritime safety. It employs the Exploratory Factor Analysis to analyse the 17 deficiency items obtained from the Tokyo Memorandum of Understandings (MoU) and extracts three hidden variables representing different ship defect levels. The Bayesian network method is then adopted to establish the ship accident model considering the dynamic ship defect levels. After credibility and sensitivity tests of the model, the estimated results verify the dynamics of the three defect level variables and their effects on ship accident. Specifically, high levels of safety and labour condition related defects significantly increase the accident rate, and both of them are noticeably influenced by historical inspection records as well. It also discloses the improvement of defect levels for ships that have been detained in the first inspection. So, specific and diversified designation of the detain policy accordingly would be more effective in improving ship safety. These provide references for port authorities to optimize the inspection process and ultimately improve ship quality and prevent maritime accidents.

Suggested Citation

  • Fan, Lixian & Zhang, Meng & Yin, Jingbo & Zhang, Jinfen, 2022. "Impacts of dynamic inspection records on port state control efficiency using Bayesian network analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:reensy:v:228:y:2022:i:c:s0951832022003763
    DOI: 10.1016/j.ress.2022.108753
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    References listed on IDEAS

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    1. Dinis, D. & Teixeira, A.P. & Guedes Soares, C., 2020. "Probabilistic approach for characterising the static risk of ships using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
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