Cumulative Correspondence Analysis as a tool for optimize factor setting in public transport

In public transport an improvement of the customer satisfaction can attract further users and individual transport would be used less. Most studies of customer satisfaction deal with ordered categorical data. The aim of this paper is to propose Cumulative correspondence analysis as a tool to develop a procedure for choosing the optimal categorical response in a multifactor state system. We briefly review the cumulative correspondence analysis and the Taguchi’s statistic and by a case study, recording the choice of the best scenario for a train service, we illustrate the proposed approach.