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A multi-layered risk exposure assessment approach for the shipping industry

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  • Vander Hoorn, Stephen
  • Knapp, Sabine

Abstract

Maritime administration and coastal states have become more aware of the need to enhance risk mitigation strategies primarily due to increased worldwide shipping activities, changing safety qualities of the world fleet and limited resources to deploy mitigation strategies. This paper introduces an innovative multi-layered framework to assess, predict and mitigate potential harm. The proposed approach addresses known restrictions of risk assessments in shipping. These restrictions are the lack of scalability to apply risk assessments over large areas using an automated routine, the absence of recognizing that the world fleet is heterogeneous, the lack of integrating location specific environmental conditions such as wind, currents or waves and most importantly, the lack of recognizing the uncertainties associated with each factor especially for predictions. The proposed framework is based on the idea of integrating various layers representing the most important factors that can influence risk in order to estimate and predict risk exposure for a given area. As proof of concept of the underlying ideas, the outcome of a pilot project with the Australian Maritime Safety Authority is presented which demonstrates the integration of the first two layers and is based on a unique and comprehensive combination of data. The results of selected endpoints of risk exposure compare well with observations. The article also discusses the integration of the remaining layers including the recognition and addition of uncertainties in the future.

Suggested Citation

  • Vander Hoorn, Stephen & Knapp, Sabine, 2015. "A multi-layered risk exposure assessment approach for the shipping industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 21-33.
  • Handle: RePEc:eee:transa:v:78:y:2015:i:c:p:21-33
    DOI: 10.1016/j.tra.2015.04.032
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    References listed on IDEAS

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    1. Bijwaard, Govert E. & Knapp, Sabine, 2009. "Analysis of ship life cycles--The impact of economic cycles and ship inspections," Marine Policy, Elsevier, vol. 33(2), pages 350-369, March.
    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.
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    Cited by:

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    3. Xueni Gou & Jasmine Siu Lee Lam, 2019. "Risk analysis of marine cargoes and major port disruptions," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(4), pages 497-523, December.
    4. 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.
    5. Knapp, S. & van de Velden, M., 2021. "Exploration of machine learning algorithms for maritime risk applications," Econometric Institute Research Papers 2021-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Knapp, S., 2020. "Quantification and analysis of risk exposure in the maritime industry," Econometric Institute Research Papers EI 2020-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Jonathan Doh & Pawan Budhwar & Geoffrey Wood, 2021. "Long-term energy transitions and international business: Concepts, theory, methods, and a research agenda," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(5), pages 951-970, July.
    8. Hosack, Geoffrey R. & Hayes, Keith R. & Barry, Simon C., 2017. "Prior elicitation for Bayesian generalised linear models with application to risk control option assessment," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 351-361.
    9. Gino J. Lim & Jaeyoung Cho & Selim Bora & Taofeek Biobaku & Hamid Parsaei, 2018. "Models and computational algorithms for maritime risk analysis: a review," Annals of Operations Research, Springer, vol. 271(2), pages 765-786, December.
    10. Yu, Ming-Miin & Chen, Li-Hsueh, 2016. "Centralized resource allocation with emission resistance in a two-stage production system: Evidence from a Taiwan’s container shipping company," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 650-671.
    11. Knapp, S. & Vander Hoorn, S., 2017. "A multi-layered risk estimation routine for strategic planning and operations for the maritime industry," Econometric Institute Research Papers EI2017-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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