This study aimed to determine relationships among risk factors influencing container port operation using Bayesian network. Risk factors identified from prior studies were classified into five groups: human error, machinery error, environmental risk, security risk, and natural disasters. Panel experts discussed identified risk factors to fulfil conditional probability tables of the interdependence model. The interdependence model was also validated by sensitivity analysis and provided an interrelation of factors influencing the direction of each other. Results of the interdependence model were partially in line with results from prior studies while practices in the global port industry confirmed interrelationships of risk factors. In addition, the relationship between top-ranked risk factors can provide a schematic drawing of the model. Accordingly, results of this study can expand the prior research in the Korean port industry, which may help port authorities improve risk management and reduce losses from the risk.
1. Introduction
2. Literature review
3. Methodology: Bayesian network (BN)
4. Results
5. Conclusion
Acknowledgements
References
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