A multi-layered risk exposure assessment approach for the shipping industry
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.
|Keywords||Binary logistic regression, Incident models, Monetary value at risk, Spatial statistics, Total risk exposure, Uncertainties|
|Persistent URL||dx.doi.org/10.1016/j.tra.2015.04.032, hdl.handle.net/1765/92180|
|Journal||Transportation Research. Part A: Policy & Practice|
Vander Hoorn, S, & Knapp, S. (2015). A multi-layered risk exposure assessment approach for the shipping industry. Transportation Research. Part A: Policy & Practice, 78, 21–33. doi:10.1016/j.tra.2015.04.032