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An integrated risk estimation methodology: Ship specific incident type risk

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  • Knapp, S.

Abstract

Shipping activity has increased worldwide, including parts of Australia, and maritime administrations are trying to gain a better understanding of total risk exposure in order to mitigate risk. Total risk exposure integrates risk at the individual ship level, risk due to vessel traffic densities, physical environmental criteria, and environmental sensitivities. A comprehensive and robust risk exposure metric can be beneficial to maritime administrations to enhance mitigation of potential harm and reduce vulnerability to the marine environment as well as to safeguard lives and property. This report outlines an integrated methodology to estimate total risk exposure, with specific attention for the ship specific risk for different types of incident. Some related application aspects of the models are discussed.

Suggested Citation

  • Knapp, S., 2013. "An integrated risk estimation methodology: Ship specific incident type risk," Econometric Institute Research Papers EI 2013-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:39596
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    Cited by:

    1. Ji, X. & Brinkhuis, J. & Knapp, S., 2014. "A method to measure enforcement effort in shipping with incomplete information," Econometric Institute Research Papers EI 2014-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Carey, J.M. & Knapp, S. & Irving, P., 2014. "Assessing ecological sensitivities of marine assets to oil spill by means of expert knowledge," Econometric Institute Research Papers EI2014-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Knapp, S. & Heij, C. & Henderson, R. & Kleverlaan, E., 2013. "Ship incident risk in the areas of Tubbataha and Banc d’Arguin: A case for designation as Particular Sensitive Sea Area?," Econometric Institute Research Papers EI2013-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Heij, C. & Knapp, S., 2018. "Predictive power of inspection outcomes for future shipping accidents," Econometric Institute Research Papers EI2018-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Knapp, S. & Heij, C., 2016. "Evaluation of total risk exposure and insurance premiums in the maritime industry," Econometric Institute Research Papers EI-1661, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Ji, Xichen & Brinkhuis, Jan & Knapp, Sabine, 2015. "A method to measure enforcement effort in shipping with incomplete information," Marine Policy, Elsevier, vol. 60(C), pages 162-170.
    7. Lutz Kretschmann, 2020. "Leading indicators and maritime safety: predicting future risk with a machine learning approach," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-22, December.

    More about this item

    Keywords

    binary logistic model; company risk estimation; incident models; total risk exposure; visualization of risk dimensions;
    All these keywords.

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