Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods
Abstract This paper presents the first application of Altman's Z''-Score EMS and Ohlson's O-Score models to predict financial distress for unlisted food companies in Colombia, the first such case for an emerging Latin American economy. Based on the above, it analyzes 147 firms fr...
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Sustainability |
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| Online Access: | https://doi.org/10.1007/s43621-025-01348-w |
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| author | Carmen Sánchez-Almeyda Jairo González-Bueno Viktor Koval Nydia Reyes-Maldonado Halyna Kryshtal Olena Zharikova |
| author_facet | Carmen Sánchez-Almeyda Jairo González-Bueno Viktor Koval Nydia Reyes-Maldonado Halyna Kryshtal Olena Zharikova |
| author_sort | Carmen Sánchez-Almeyda |
| collection | DOAJ |
| description | Abstract This paper presents the first application of Altman's Z''-Score EMS and Ohlson's O-Score models to predict financial distress for unlisted food companies in Colombia, the first such case for an emerging Latin American economy. Based on the above, it analyzes 147 firms from 2016 to 2023, identifying their financial trends and categorizing them into distressed, gray, and safe zones. This is a dual-model approach designed to bridge this important gap in the literature with actionable insights on the vulnerabilities of a sector vital for both economic stability and food security for the nation of Colombia. Results show that 64.57% of firms each year fall into a safe zone characterized by excellent financial health and stability against adverse conditions. About 20.41% fall within the gray zone, representing moderate financial health with the potential to slide further without timely and appropriate interventions. While the remaining 16.07% represent the distressed zone, they show imminent signs of insolvency or default. Including variables like solvency and profitability trends in the Ohlson model increases its predictive sensitivity and, therefore, identifies a slightly higher percentage of distressed firms than the Z''-Score model. They provide recommendations regarding the improvement of credit access, enabling innovation, and restructuring operational areas to consolidate profitability and both short- and long-term solvency. The same idea can be further checked by using more advanced predictive tools like hybrid models and longitudinal analyses in future studies. Such a finding provides a full-scale framework of analysis regarding financial health. It boosts interest by policymakers and stakeholders in the sustainable development of industries supporting food production in Colombia among firms operating in emerging markets. |
| format | Article |
| id | doaj-art-5463ab2ee985415aaa423b06ed2bc454 |
| institution | Kabale University |
| issn | 2662-9984 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Sustainability |
| spelling | doaj-art-5463ab2ee985415aaa423b06ed2bc4542025-08-20T03:45:43ZengSpringerDiscover Sustainability2662-99842025-07-016111810.1007/s43621-025-01348-wPredicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methodsCarmen Sánchez-Almeyda0Jairo González-Bueno1Viktor Koval2Nydia Reyes-Maldonado3Halyna Kryshtal4Olena Zharikova5Faculty of Economics and Business, Universidad Autónoma de BucaramangaFaculty of Economics and Business, Universidad Autónoma de BucaramangaDepartment of Business and Tourism Management, Izmail State University of HumanitiesFaculty of Economics and Business, Universidad Autónoma de BucaramangaDepartment of Finance, Banking and Insurance, Interregional Academy of Personnel ManagementDepartment of Banking and Insurance, National University of Life and Environmental Science of UkraineAbstract This paper presents the first application of Altman's Z''-Score EMS and Ohlson's O-Score models to predict financial distress for unlisted food companies in Colombia, the first such case for an emerging Latin American economy. Based on the above, it analyzes 147 firms from 2016 to 2023, identifying their financial trends and categorizing them into distressed, gray, and safe zones. This is a dual-model approach designed to bridge this important gap in the literature with actionable insights on the vulnerabilities of a sector vital for both economic stability and food security for the nation of Colombia. Results show that 64.57% of firms each year fall into a safe zone characterized by excellent financial health and stability against adverse conditions. About 20.41% fall within the gray zone, representing moderate financial health with the potential to slide further without timely and appropriate interventions. While the remaining 16.07% represent the distressed zone, they show imminent signs of insolvency or default. Including variables like solvency and profitability trends in the Ohlson model increases its predictive sensitivity and, therefore, identifies a slightly higher percentage of distressed firms than the Z''-Score model. They provide recommendations regarding the improvement of credit access, enabling innovation, and restructuring operational areas to consolidate profitability and both short- and long-term solvency. The same idea can be further checked by using more advanced predictive tools like hybrid models and longitudinal analyses in future studies. Such a finding provides a full-scale framework of analysis regarding financial health. It boosts interest by policymakers and stakeholders in the sustainable development of industries supporting food production in Colombia among firms operating in emerging markets.https://doi.org/10.1007/s43621-025-01348-wFinancial distressAltman’s Z-Score EMSOhlson’s O-ScoreFood production sectorColombian economy |
| spellingShingle | Carmen Sánchez-Almeyda Jairo González-Bueno Viktor Koval Nydia Reyes-Maldonado Halyna Kryshtal Olena Zharikova Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods Discover Sustainability Financial distress Altman’s Z-Score EMS Ohlson’s O-Score Food production sector Colombian economy |
| title | Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods |
| title_full | Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods |
| title_fullStr | Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods |
| title_full_unstemmed | Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods |
| title_short | Predicting financial distress in the food production sector: a dual-model approach using Z-score and O-score methods |
| title_sort | predicting financial distress in the food production sector a dual model approach using z score and o score methods |
| topic | Financial distress Altman’s Z-Score EMS Ohlson’s O-Score Food production sector Colombian economy |
| url | https://doi.org/10.1007/s43621-025-01348-w |
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