This paper addresses the importance of industry-specific models for SMEs bankruptcy prediction, building on earlier research finding larger predictive accuracy and enhanced temporal stability. Using Italian data, we propose separate bankruptcy prediction models for a few industries based on balance sheet data and explore the predictive power of SMEs' website html code structure. Our findings suggest that website data can serve as a valid complementary source for bankruptcy prediction, with different performances across sectors. We observe a certain degree of sectoral heterogeneity in the importance of financial ratios, firm-specific characteristics, and website structure, calling for an industry-tailored approach in bankruptcy prediction models.

Bottai, C., Crosato, L., Liberati, C. (2024). Prediction of SMEs Bankruptcy at the Industry Level with Balance Sheets and Website Indicators. In Proceedings CARMA 2024 - 6th International Conference on Advanced Research Methods and Analytics (pp.235-241). Editorial Universitat Politècnica de València [10.4995/carma2024.2024.17761].

Prediction of SMEs Bankruptcy at the Industry Level with Balance Sheets and Website Indicators

Bottai, Carlo;Liberati, Caterina
2024

Abstract

This paper addresses the importance of industry-specific models for SMEs bankruptcy prediction, building on earlier research finding larger predictive accuracy and enhanced temporal stability. Using Italian data, we propose separate bankruptcy prediction models for a few industries based on balance sheet data and explore the predictive power of SMEs' website html code structure. Our findings suggest that website data can serve as a valid complementary source for bankruptcy prediction, with different performances across sectors. We observe a certain degree of sectoral heterogeneity in the importance of financial ratios, firm-specific characteristics, and website structure, calling for an industry-tailored approach in bankruptcy prediction models.
paper
website data, HTML code, SMEs, supervised learning.
English
CARMA 2024 - 6th International Conference on Advanced Research Methods and Analytics - June 26, 2024 – June 28, 2024
2024
Domenech, J; Vicente, M R; de Pedraza, P
Proceedings CARMA 2024 - 6th International Conference on Advanced Research Methods and Analytics
2024
235
241
none
Bottai, C., Crosato, L., Liberati, C. (2024). Prediction of SMEs Bankruptcy at the Industry Level with Balance Sheets and Website Indicators. In Proceedings CARMA 2024 - 6th International Conference on Advanced Research Methods and Analytics (pp.235-241). Editorial Universitat Politècnica de València [10.4995/carma2024.2024.17761].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/494760
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