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Comparative analysis of the impact of new inspection regime on port state control inspection

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  • Yang, Zhisen
  • Yang, Zaili
  • Teixeira, Angelo Palos

Abstract

As an administrative measure to ensure maritime safety, Port State Control inspections are implemented and regarded as an important line of defence in coping with potential maritime accidents. To reinforce its role, a New Inspection Regime (NIR) was developed and put into practice by Paris MoU in 2011. It is widely recognized that the implementation of NIR has transformed and modernized the PSC inspection system in the Paris MoU region, stimulated the vessel qualit, and further improved vessel quality. In this paper, the influence of the implementation of NIR on the PSC inspection system and vessel quality is revealed for the first time. Based on inspection data and records collected from the Paris MoU online database, a comparative analysis between the ‘Pre-NIR’ (time before the implementation of NIR) and ‘Post-NIR’ (time after the implementation of NIR) periods is conducted from two perspectives. A macroscopic approach is first adopted to characterise the overall changes in inspection results and inspected vessels' quality through a statistical analysis of extrinsic Key Performance Indicators (KPIs) such as detention rate and deficiency rate. Then, a microscopic analysis is conducted to assess the influence of the NIR on intrinsic attributes of the vessels and of the inspection results based on Bayesian Network models derived from Pre-NIR and Post-NIR periods. The findings of this research systematically reveal the aspects from which the NIR improves the PSC inspection system, vessel quality and maritime safety. It will generate significant impact on and contribution to the promotion and stimulation of the adoption of NIR in more ports and regions to improve safety at sea in the whole world.

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  • Yang, Zhisen & Yang, Zaili & Teixeira, Angelo Palos, 2020. "Comparative analysis of the impact of new inspection regime on port state control inspection," Transport Policy, Elsevier, vol. 92(C), pages 65-80.
    • Handle: RePEc:eee:trapol:v:92:y:2020:i:c:p:65-80
    DOI: 10.1016/j.tranpol.2020.04.009
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    References listed on IDEAS

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    Cited by:

    1. Liu, Kezhong & Yu, Qing & Yang, Zhisen & Wan, Chengpeng & Yang, Zaili, 2022. "BN-based port state control inspection for Paris MoU: New risk factors and probability training using big data," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    2. Rong, H. & Teixeira, A.P. & Guedes Soares, C., 2022. "Maritime traffic probabilistic prediction based on ship motion pattern extraction," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    3. Yang, Zhisen & Yu, Qing & Yang, Zaili & Wan, Chengpeng, 2024. "A data-driven Bayesian model for evaluating the duration of detention of ships in PSC inspections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    4. Yu, Qing & Teixeira, Ângelo Palos & Liu, Kezhong & Rong, Hao & Guedes Soares, Carlos, 2021. "An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Yang, Zhisen & Wan, Chengpeng & Yu, Qing & Yin, Jingbo & Yang, Zaili, 2023. "A machine learning-based Bayesian model for predicting the duration of ship detention in PSC inspection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    6. Wang, Yuhong & Zhang, Fan & Yang, Zhisen & Yang, Zaili, 2021. "Incorporation of deficiency data into the analysis of the dependency and interdependency among the risk factors influencing port state control inspection," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    7. Yang, Zhisen & Wan, Chengpeng & Yang, Zaili & Yu, Qing, 2021. "Using Bayesian network-based TOPSIS to aid dynamic port state control detention risk control decision," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    8. Antão, P. & Sun, S. & Teixeira, A.P. & Guedes Soares, C., 2023. "Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    9. 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).
    10. Zhu, Jiang-Hong & Yang, Qiang & Jiang, Jun, 2023. "Identifying crucial deficiency categories influencing ship detention: A method of combining cloud model and prospect theory," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    11. 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).
    12. Yan, Ran & Mo, Haoyu & Guo, Xiaomeng & Yang, Ying & Wang, Shuaian, 2022. "Is port state control influenced by the COVID-19? Evidence from inspection data," Transport Policy, Elsevier, vol. 123(C), pages 82-103.

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