Multidimensional Analysis of Customer Satisfaction Data: The Scaling Problems

In the analysis of Customer Satisfaction (CS) often we have to treat at the same time data having different kind of scale. In order to obtain a measure of the quality level perceived/expected a conventional ordinal rating scale for each attribute of a service is used in literature. Moreover additional information on the users or on the objective characteristics of the service is available (interval, ordinal and or categorical scale). In the latter the importance or weight assigned to the different items it must be also considered (compositional scale). To analyse these different kind of data particularly precaution should be used. A transformation of quality level perceived/expected data in quantitative scale is carried out before a multidimensional data analysis. In literature more techniques are proposed for the quantification of ordinal data preserving the original characteristics of this data. Aims of this paper are to analyse different ways to quantify ordinal data, and illustrate how the additional information on the customers or on the service could be used in the multidimensional analysis as external information.