This chapter develops a framework that uses fuzzy set theory in order to measure customersatisfaction, starting from a survey with several questions. The basic concepts of the theoryof the fuzzy numbers are briefly described. A criterion based on the sampling cumulativefunction, which assigns values to the membership function with reference to each quantitative,ordinal and binary variable, is suggested.Weighting and aggregation operators for the variablesare considered. An application to ABC survey data shows the usefulness of the fuzzy setapproach: the gradual transition from very dissatisfied to really satisfied customers is capturedby fuzzy composite indices. The comparison with the classical methods for the measurementof customer satisfaction highlights the advantages of the suggested criterion from both thetheoretical and operational points of view.
Fuzzy methods and satisfaction index / S., Zani; M. A., Milioli; Morlini, Isabella. - STAMPA. - (2012), pp. 439-455.
Fuzzy methods and satisfaction index
MORLINI, Isabella
2012
Abstract
This chapter develops a framework that uses fuzzy set theory in order to measure customersatisfaction, starting from a survey with several questions. The basic concepts of the theoryof the fuzzy numbers are briefly described. A criterion based on the sampling cumulativefunction, which assigns values to the membership function with reference to each quantitative,ordinal and binary variable, is suggested.Weighting and aggregation operators for the variablesare considered. An application to ABC survey data shows the usefulness of the fuzzy setapproach: the gradual transition from very dissatisfied to really satisfied customers is capturedby fuzzy composite indices. The comparison with the classical methods for the measurementof customer satisfaction highlights the advantages of the suggested criterion from both thetheoretical and operational points of view.File | Dimensione | Formato | |
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