Profitability analysis using IDEA–DA framework

The purpose of this paper is to propose a framework of imprecise data envelopment analysis–discriminant analysis (IDEA–DA) to deal with the profitability analysis of 31 chain stores belonging to a hairdressing company, known as company $$L$$ L , in central Taiwan. Return on investment (ROI) is used as the measure of profitability. Five predictor variables are adopted to establish the discriminant function. Five classification types (i.e., 2-group, 3-group, 4-group, 5-group and 6-group) are included in the experiments. The results show that the proposed discriminant function is a robust one with respect to the rankings obtained under different classification types; moreover, the 4-group type is suitable to classify the ROI and it acquires a satisfactory apparent rate. Hence, the 4-group type is suggested in practice work. The study shows the proposed IDEA–DA is an effective tool for company $$L$$ L to conduct the profitability analysis. By firstly discriminating the ROI data collected, consequently showing the aspects for improving ROI, and then use this tool at certain check points in the next year to predict the ROI levels of the stores for the upcoming whole year. For the store which is predicted to be group member with a low or very low ROI level, timely reforms could be made for improving the ROI level of the whole year. The proposed model can also be used to deal with the similar problems for the other chain-store systems which possess the analogue characteristic. Copyright Springer Science+Business Media New York 2014