Abstract
Port state control (PSC) inspection acts as a safeguard against maritime accidents and marine environment pollution. Due to limited inspection resources and high inspection costs, port states can only select substandard ships with high risk for inspection. Therefore, efficient and accurate identification of substandard ships is important. This study reviews the current ship selection methods used in different ports and proposed in the existing literature, then discusses their advantages and disadvantages. Based on this review, a combined model for ship risk prediction considering ship deficiencies and detention is developed and validated in this study. Reasonable and comprehensive comparisons of the proposed combined model and the current ship selection method at the Port of Hong Kong are conducted. The comparison results provide managerial insights and suggestions for Memorandum of Understandings (MoUs). This study is the first to review the ship selection methods implemented in port states and proposed in the PSC inspection literature. It is also the first study to combine the number of ship deficiencies and the probability of detention in a unified model to calculate ship risk. This study is valuable for improving the efficiency of ship selection in MoUs and thus protecting maritime transport.
| Original language | English |
|---|---|
| Pages (from-to) | 600-615 |
| Number of pages | 16 |
| Journal | Maritime Policy and Management |
| Volume | 49 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jun 2022 |
Keywords
- machine learning in maritime transportation
- Port state control
- ship deficiency
- ship detention
- ship selection
ASJC Scopus subject areas
- Geography, Planning and Development
- Transportation
- Ocean Engineering
- Management, Monitoring, Policy and Law
