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Econometric analysis on the effect of port state control inspections on the probability of casualty: Can targeting of substandard ships for inspections be improved?

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  • Knapp, Sabine
  • Franses, Philip Hans

Abstract

This article is based on 183,819 port state control inspections from various port state control regimes and casualties from three different data sources for a time period of 6 years. It is the first time an analysis on a combined dataset of this magnitude has been performed. Binary logistic regression is used to measure the effect of inspections on the probability of casualty, which can be measured for very serious casualties but not for serious or less serious casualties. In addition, the magnitude of improvement areas for targeting substandard vessels is determined and the models further show how targeting of substandard ships on a combined dataset can be improved. In addition, the analysis also compares the fishing fleet with the commercial fleet.

Suggested Citation

  • Knapp, Sabine & Franses, Philip Hans, 2007. "Econometric analysis on the effect of port state control inspections on the probability of casualty: Can targeting of substandard ships for inspections be improved?," Marine Policy, Elsevier, vol. 31(4), pages 550-563, July.
    • Handle: RePEc:eee:marpol:v:31:y:2007:i:4:p:550-563
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    Citations

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    Cited by:

    1. Jose Manuel Prieto & Victor Amor & Ignacio Turias & David Almorza & Francisco Piniella, 2021. "Evaluation of Paris MoU Maritime Inspections Using a STATIS Approach," Mathematics, MDPI, vol. 9(17), pages 1-13, August.
    2. Jose Manuel Prieto & Víctor Amor-Esteban & David Almorza-Gomar & Ignacio Turias & Francisco Piniella, 2023. "Application of Multivariate Statistical Techniques as an Indicator of Variability of the Effects of COVID-19 on the Paris Memorandum of Understanding on Port State Control," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    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. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    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. Fan, Lixian & Luo, Meifeng & Yin, Jinbo, 2014. "Flag choice and Port State Control inspections—Empirical evidence using a simultaneous model," Transport Policy, Elsevier, vol. 35(C), pages 350-357.
    8. Yang, Zhisen & Yang, Zaili & Yin, Jingbo & Qu, Zhuohua, 2018. "A risk-based game model for rational inspections in port state control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 477-495.
    9. Xiao, Yi & Wang, Grace & Ge, Ying-En & Xu, Qinyi & Li, Kevin X., 2021. "Game model for a new inspection regime of port state control under different reward and punishment conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    10. Heij, C. & Bijwaard, G.E. & Knapp, S., 2010. "Ship Inspection Strategies: Effects on Maritime Safety and Environmental Protection," Econometric Institute Research Papers EI 2010-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Wang, Shuaian & Yan, Ran & Qu, Xiaobo, 2019. "Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 129-157.
    12. Xiao, Yi & Qi, Guanqiu & Jin, Mengjie & Yuen, Kum Fai & Chen, Zhuo & Li, Kevin X., 2021. "Efficiency of Port State Control inspection regimes: A comparative study," Transport Policy, Elsevier, vol. 106(C), pages 165-172.
    13. 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.
    14. Knapp, S. & Bijwaard, G.E. & Heij, C., 2010. "Estimated Incident Cost Savings in Shipping Due to Inspections," Econometric Institute Research Papers EI 2010-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Esma Gül Emecen Kara, 2016. "Risk Assessment in the Istanbul Strait Using Black Sea MOU Port State Control Inspections," Sustainability, MDPI, vol. 8(4), pages 1-17, April.

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