An Ordinal Regression Method for Multicriteria Analysis of Customer Satisfaction

The purpose of this paper is to present and test an ordinal regression method for multicriteria analysis of customer satisfaction, developed from our study of the MUSA (MUlticriteria Satisfaction Analysis) method. The proposed method also aggregates the individual customer satisfaction criteria into an overall value function, but it makes use of a dummy variable regression technique with additional constraints. For the same input information, the outputs of the proposed method are more stable than the outputs of MUSA and the differences observed allowed us to have a deeper knowledge on how to handle the input preference information provided by the customers. Moreover, contrary to MUSA, we propose to apply more than one regression technique, starting with a dummy variable regression technique employing the least squares approach and then iteratively use a robust method of regression such as M-regression. The main features of this approach are discussed in the paper.