Financial determinants of credit risk in the logistics and shipping industries

• Main Authors: Woo, Su-Han, Kwon, Min-Su, Yuen, Kum Fai
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Maritime studies; Credit Risk Analysis; Panel Data Regression
• Online Access: https://hdl.handle.net/10356/155452
• Institution: Nanyang Technological University

This study examines factors affecting the credit risk of global logistics and shipping companies using Altman’s Z-score and Ohlson’s O-score models. Panel data multiple regression analysis is conducted to evaluate the impacts of various financial ratios on credit risk for both industries and to assess their unique characteristics. We find that while credit risk is, on average, similar between the shipping and logistics industries, the variability in credit risk in the shipping industry is much higher. We also find that while both equity and current ratios have a significant impact on credit risk in both industries, return on assets and the quick ratio have the most significant impact on the logistics and maritime industries, respectively. There are slight differences in the determinants of credit risk when analyses are further segmented into different regions (i.e., Asia, EU, USA and Africa). This study introduces scientific models and recommends financial indicators for financiers to evaluate the credit risk of both industries, help improve decision-making, and minimize the probability of default by debtors.