Using Corporate Social Responsibility Orientation Characteristics for Small Enterprise Default Prediction

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Abstract: This study aims to analyse whether the characteristics of a company’s corporate social responsibility (CSR) orientation could improve the accuracy rates of small enterprise (SE) bankruptcy prediction models. A sample made up of 382 Italian SEs is analysed and, by applying logistic regression, a SE default prediction model is designed using both CSR orientation characteristics and financial ratios as default predictors. The accuracy of this model is then compared to that of a second model based only on financial ratios as predictive variables. The main results are: i) using CSR orientation characteristics significantly improves the effectiveness of SE default prediction modelling; ii) the smaller a firm the higher the increase in the prediction accuracy that can be obtained by using CSR characteristics as default predictors; iii) SE default prediction modelling should be separately implemented for different size groups of firms.

WSEAS Transactions on Business and Economics, ISSN / E-ISSN: 1109-9526 / 2224-2899, Volume 15, 2018, Art. #13

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Francesco Ciampi, "Using Corporate Social Responsibility Orientation Characteristics for Small Enterprise Default Prediction," WSEAS Transactions on Business and Economics, vol. 15, pp. 113-127, 2018, DOI:
Francesco Ciampi. Using Corporate Social Responsibility Orientation Characteristics for Small Enterprise Default Prediction. WSEAS Transactions on Business and Economics. 2018;15:113-127.
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