A Bayesian Approach for integrating organisational factors in risk analysis: A case study in maritime

The paper presents an innovative approach to integrate human and organisational factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the maritime transport system (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The last ones have been modelled by means of a set of variables whose combinations express the relevant functions performed by each actor. The Bayesian Belief Network model of the maritime transport system has been used in a case study for the quantification of human and organisational factors in the risk analysis carried out at the preliminary design stage of high speed craft (HSC). The analysis has focused on the frequency assessment of collision, grounding, contact and striking events by means of a Fault Tree Analysis (FTA). The approach allowed identification of probabilistic correlations between the basic events and the Bayesian Belief Network model of the maritime transport system, representing the operational and organisational scenario. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the Bayesian Belief Network have been estimated by means of experts' judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis was carried out over the model to identify configurations of the maritime transport system leading to a significant reduction of accident probability during the operation of the high speed craft. © 2006 Taylor & Francis Group.