A multi-layered risk estimation routine for strategic planning and operations for the maritime industry

Sabine Knapp and Stephen Vander Hoorn

No EI2017-02, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: Maritime regulators and port authorities require the ability to predict risk exposure for strategic planning aspects to optimize asset allocation, mitigate and prevent incidents. This article builds on previous work to develop the strategic planning component and introduces the concept of a multilayered risk estimation framework (MLREF) for strategic planning and operations. The framework accounts for most of the risk factors such as ship specific risk, vessel traffic densities and met ocean conditions and allows the integration of the effect of risk control option and a location specific spatial rate ratio to allow for micro level risk assessments. Both, the macro (eg. covering larger geographic areas or EEZ) and micro level application (eg. passage way, particular route of interest) of MLREF was tested via a pilot study for the Australian region using a comprehensive and unique combination of dataset. The underlying routine towards the development of a strategic planning tool was developed and tested in R. Applications of the layers for the operational part such as an automated alert system and sources of uncertainties for risk assessments in general are described and discussed along with future developments and improvements.

Keywords: Total risk exposure; binary logistic regression; spatial statistics; incident models; uncertainties; strategic planning; operational alerts; drift groundings; collisions; powered groundings; prediction routines (search for similar items in EconPapers)
Pages: 19
Date: 2017-02-01
New Economics Papers: this item is included in nep-rmg and nep-tre
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