Neural networks analysis in business failure prediction of Chinese importers: A between-countries approach

The results show that the neural network models provide good classification capability in both cross-industry and industry-specific contexts. Moreover, the higher the training sample size and the larger the number of hidden nodes, the higher the classification rates, the lower the Type I error rates, the lower the relative CI/CII ratios. Among the three variables selection methods, factor analysis is superior to stepwise discriminant analysis (SDA) and ALL in terms of classification accuracy, generalization ability and error costs, while SDA provides the worst performance in all situations.