MUSA-INT: Multicriteria customer satisfaction analysis with interacting criteria

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• 作者：Silvia Angilella ; Salvatore Corrente ; Salvatore Greco ; Roman S?owi¨½ski
• 关键词：Multiple criteria decision aiding ; Customer satisfaction analysis ; Utility function ; Interacting criteria ; Ordinal scales
• 刊名：Omega
• 出版年：2014
• 出版时间：January, 2014
• 年：2014
• 卷：42
• 期：1
• 页码：189-200
• 全文大小：525 K

文摘

We are considering the problem of measuring and analyzing customer satisfaction concerning a product or a service evaluated on multiple criteria. The proposed methodology generalizes the MUSA (MUlticriteria Satisfaction Analysis) method. MUSA is a preference disaggregation method that, following the principle of ordinal regression analysis, finds an additive utility function representing both the comprehensive satisfaction level of a set of customers and a marginal satisfaction level with respect to each criterion. Differently from MUSA, the proposed approach, that we will call MUSA-INT, takes also into account positive and negative interactions among criteria, similarly to the multicriteria method UTA^GMS-INT. Our method accepts evaluations on criteria with different ordinal scales which do not need to be transformed into a unique cardinal scale prior to the analysis. Moreover, instead of a single utility function, MUSA-INT can also take into account a set of utility functions representing customers' satisfaction, adopting the robust ordinal regression methodology. An illustrative example shows how the proposed methodology can be applied on a customers¡¯ survey.