운송 서비스 유형별 해운업 파산예측에 관한 연구
Bankruptcy Prediction Models Based on Shipping Service Types
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참고문헌
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초록
본 연구는 해운업에서 운송 서비스 유형별(컨테이너, 벌크, 탱커) 파산 예측 모델을 개발하고, 주요 리스크 요인을 비교 분석하였다. 전통적인 통계 모델과 최신 머신러닝 기법(XGBoost, LightGBM, CatBoost 등)을 활용하여 각 유형의 예측 성능을 평가하였으며, SHAP 분석을 통해 변수 중요도를 시각화하였다. 연구 결과, 서비스 유형별 주요 리스크 요인이 상이하게 나타났으며, 각 유형에 특화된 맞춤형 리스크 관리 전략의 필요성을 시사한다. 본 연구는 해운업의 재무 안정성 강화를 위한 기초 자료를 제공한다.
Abstract
This study develops bankruptcy prediction models for various types of shipping services (container, bulk, and tanker) and compares the key risk factors associated with each. By utilizing traditional statistical models alongside advanced machine learning techniques, such as XGBoost, LightGBM, and CatBoost, we evaluated the predictive performance of each service type. SHAP analysis was applied to visualize variable importance. The findings reveal significant differences in key risk factors by service type, highlighting the need for tailored risk management strategies for each segment. This study provides foundational insights to enhance the financial stability of the shipping industry.
참고문헌 (12)
- Altman, E. I., "Financial ratios, discriminant analysis and the prediction of corporate bankruptcy", The Journal of Finance, 23(4), pp.589~609 (1968)
- Cho, I. S., "A Study of Financial Ratios Change of Korean Dry Bulk Shipping Firms before and after 2008 Global Financial Crisis", Journal of Korean Navigation and Port Research, 44(3), pp.244~252 (2008)
- Kim, J. H., "A study on Classification Models for Predicting Bankruptcy Based on XAI", KIPS Transactions on Software and Data Engineering, 12(8), pp.333~340 (2023)
- Kim, M. H., "A Study on the Failing Prediction of Korean Shipping Companies", Journal of Maritime Business, 34 (2016)
- Kim, S. J., "Application of Random Forests to Corporate Credit Rating Prediction", Journal of Industrial Innovation, 32(1), pp.187~211 (2016)
- Kwon, S. M., "A Study on the Credit Rating Prediction for Export Manufacturing Companies, Using Machine Learning and Artifical Neural Network", The International Commerce & Law Review, 98(5), pp.229~248 (2023)
- Lee, S. Y., "Effects of Economic Conditions on Capital Structure : Evidence from Korean Shipping Firms", Journal of Korean Navigation and Port Research, 40(6), pp.451~458 (2018)
- Molnar, C., "Interpretable machine learning" (2020), Lulu. com
- Stopford, M., "Maritime Economics" (2008), Routledge
- Yoon, J. N., "A study of Early Warning Model in the Dry Bulk Shipping Industry Approach", Journal of Korean Navigation and Port Research, 42(1), pp.57~66 (2018)
- Shin, S. H., "Lessons from bankruptcy of Hanjin Shipping Company in chartering", Maritime Policy & Management, 46(2), pp.136~155 (2019)
- Song, D. W., "Learning from Hanjin Shipping’s failure : A holistic interpretation on its causes and reasons", Transport Policy, 82, pp.77~87 (2019)