Article2010

Predict US Restaurant Firm Failures: The Artificial Neural Network Model versus Logistic Regression Model

60 citations0/0 files storedTourism and Hospitality Research

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

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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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1966Financial Ratios As Predictors of Failure 1979Financial Managemen:t Theory and Practice 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 2018Financial Management: Theory and Practice 1999Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis 1996A survey of business failures with an emphasis on prediction methods and industrial applications

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