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- Publisher
- Emerald Publishing
- Copyright
- Copyright © Emerald Group Publishing Limited
- ISSN
- 2397-3757
- DOI
- 10.1108/MABR-12-2016-0032
- Publisher site
- See Article on Publisher Site
Abstract
PurposeThis study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.Design/methodology/approachThis paper proposes a bankruptcy prediction model by applying the hybrid of logistic regression and Bayesian probabilistic networks.FindingsThe proposed model shows its potential of contributing to a powerful tool to predict financial bankruptcy of shipping operators, and provides important insights to the maritime community as to what performance measures should be taken to ensure the shipping companies’ financial soundness under dynamic environments.Research limitations/implicationsThe model and its associated variables can be expanded to include more factors for an in-depth analysis in future when the detailed information at firm level becomes available.Practical implicationsThe results of this study can be implemented to oil tanker shipping firms as a prediction tool for bankruptcy rate.Originality/valueIncorporating quantitative statistical measurement, the application of BN in financial risk management provides advantages to develop a powerful early warning system in shipping, which has unique characteristics such as capital intensive and mobile assets, possibly leading to catastrophic consequences.
Journal
Maritime Business Review – Emerald Publishing
Published: Sep 15, 2017