Logistic Regression Model for Business Failures Prediction of Technology Industry in Thailand

Abstract

Since the large number of parties involved in corporate failure or 'business failure', the avoidance of failure has always been an important issue in the field of corporate finance and business management. In this paper, the model was developed to predict business failure in Thailand particular in technology industry by using four variables from Altman's model and adding one variable to the model. Descriptive statistics, correlation, and independent T-test are used for testing to see the characteristics of each variable on both failed and non-failed companies. The model was developed by using the stepwise logistic regression. Samples were developed by using financial information from private limited companies based on technology industry in Bangkok. The result from this empirical study can conclude that financial ratios are useful analytical techniques for forecasting financial health of companies in technology industry. The result of independent T-test has pointed out sales to total assets ratio is the only significant independent variable indicating significant differences between failed and non-failed group. The Nagelkerke R 2 indicated 42.4% of the variation in the outcome variable. The predictability accuracy of the model is 77.8% which is under 95% confidence level.