Study based on ＂Situational Rationality＂ hypothesis for customer market classification model

The traditional market segmentation was based on ＂transcendental rationality＂ or ＂Situational Rationality＂, studies shows that it had disadvantages. This paper states the ＂Situational＂ integrated rationality hypothesis and then comes up with the market segmenting models and classification algorithm basing on this hypothesis. This algorithm combined the Rough Set theory and Neural Networks in application, which overcome the dilemma that caused complicated network structure and long training time by only using Neural Networks and influenced the classification precision caused by noise disturbance by only using Rough Set methods. Finally, the paper did a comparison experiment between the traditional method and the method we came up, the results shows that the model and algorithm has its advantage on every aspects.