Dynamics of port state control and impact on ship safety: Case studies of Tokyo and Indian Ocean Memorandum of understanding

Port State Control has been regarded as a crucial safety measure for maritime and environmental safety. However, the inspection data from Tokyo Memorandum of Understanding (MoU) reveals that numerous vessels were repeatedly inspected. To investigate the underlying reasons of this, this study utilizes the Dynamic Bayesian Network (DBN) models to explore the dynamic impact of deficiencies in Tokyo and Indian Ocean MoUs on ship detention and accidents. The DBN models are based on the latest 10 inspections of individual ships. Reliability and sensitivity analyses highlight the significant effect of facility condition related risk deficiencies on detentions and accidents. It innovatively introduces a cross-MoU effect in the DBNs to investigate how an MoU’s inspection and detention influence the ship’s subsequent outcomes in the other MoU. The result uncovers differences in inspection mechanisms between MoUs regarding deficiency identification and detention activities. To prevent “smart” ships from exploiting the lack of information sharing between MoUs and to avoid accidents, it is crucial to establish more accurate and dynamic judgments through enhanced information sharing among MoUs.