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Heterogeneity Measures in Customer Satisfaction Analysis

机译:客户满意度分析中的异质性措施

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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.
机译:在本文中,我们应对通过新的观点分析客户满意度在分析客户满意度的情况下识别有效方法的问题。在文献中,通过标准偏差或变异系数来衡量客户满意度指数的可变性。以这种方式,可能掩盖客户之间的异质性。为了克服这一缺点,我们提供了一种新方法来构建客户满意度指数的异质性的多维测量,而不是根据特定异质性指数的选择。该方法基于异质性曲线,这导致多均匀性的更详细描述而不是替代措施。此外,潜在的类模型用于基于对一组项目的响应将个体分为不同组。一旦组成,客户满意度研究人员就可以得出关于异质性的满意度和团体特征的结论。

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