Cumulative correspondence analysis to improve the public train transport

Abstract

To a company, improving customer satisfaction (CS) is a strategic element to increase market share, for example in public transport a growth of users implies a positive effect as private transport reduced.
Consequently, the use of statistical methods directed to the analysis of CS is very important to get information necessary to support strategic decisions. In this paper, through Taguchi method for design of experiment, we set nine different hypothetic public train transport (called scenarios) and we asked to potential users to evaluate them by an ordinal scale. In order to analyse this data we use an integrated approach based on Cumulative Correspondence Analysis and the Taguchi's index, it allows to find a scenario that maximizes the satisfaction of potential users.