In this paper we deal with the problem of identifying a valid way to characterize heterogeneity in the analysis of customer satisfaction observing the phenomenon through a new perspective. In the literature, the variability of a Customer Satisfaction index is measured by the standard deviation or the coefficient of variation. In this way, heterogeneity among customers may be masked. To overcome this drawback, we provide a new approach to the construction of a multi-dimensional measure of heterogeneity of the Customer Satisfaction index not depending on the choice of a particular heterogeneity index. The approach is based on heterogeneity profiles which lead to a more detailed description of heterogeneity than alternative measures. Moreover, a latent class model is used for classifying individuals into distinct groups based on responses to a set of items. Once groups are formed, Customer Satisfaction researchers can make conclusions about the level of satisfaction and the characteristics of groups in terms of heterogeneity.
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