Abstract
Based on recent years' financial data of US restaurant firms, this study developed failure prediction models using logistic regression and artificial neural networks (ANNs). The findings show that the logistic model is not inferior to the ANNs model in terms of prediction accuracy. For restaurant firms, the logistic model not only provides bankruptcy prediction at an accuracy rate no inferior to that provided by the ANNs model but also indicates how firms can act to reduce the chance of going bankrupt. Therefore, for US restaurant firms the logistic model is recommended as a preferred method for predicting restaurant firm failures.
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