MUSA-INT: Multicriteria customer satisfaction analysis with interacting criteria
MUSA-INT: Multicriteria customer satisfaction analysis with interacting criteria
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DOI：
10.1016/j.omega.2013.05.006
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发表时间：
2014-01-01
影响因子：
6.9
通讯作者：
Slowinski, Roman
中科院分区：
文献类型：
--
作者：
Angilella, Silvia;Corrente, Salvatore;Slowinski, Roman
我们正在考虑测量和分析客户满意度的问题，这些满意度与产品或服务的多重标准有关。提出的方法推广了MUSA（多标准满意度分析）方法。MUSA是一种偏好分解方法，它遵循有序回归分析的原理，找到一个代表一组顾客的综合满意水平和相对于每个标准的边际满意水平的附加效用函数。与MUSA不同的是，我们将提出的方法称为MUSA-INT，它也考虑了标准之间的积极和消极相互作用，类似于多标准方法UTA(GMS)-INT。我们的方法接受评价标准与不同的序数尺度，不需要转换成一个唯一的基数尺度之前的分析。此外，除了单一的效用函数，MUSA-INT还可以考虑一组代表顾客满意度的效用函数，采用稳健有序回归方法。一个说明性的例子说明了建议的方法如何应用于客户调查。(C) 2013 Elsevier Ltd.版权所有。
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. (C) 2013 Elsevier Ltd. All rights reserved.