QFD with fuzzy and entropy weight for evaluating retail customer values

In past research on the evaluation of customer value, customers were mostly assumed to conduct aggregating partial deliberations, which were analyzed with a single step procedure, yet the research was unable to derive a whole picture of customer value. In this paper we use a wholesale store industry as an example, aiming to explore the characteristics of customer value by two research steps. Firstly, through a two-stage questionnaire and the means-end theory, it is shown that customer value can be represented as a set of self-relevant organized elements and consumers' clusters. Secondly, fuzzy judgment is used to determine the vague cognition of customer value, and fuzzy quality function deployment and entropy are used to determine the intensity of customer value to develop the competitive model. The resulting fuzzy values can be used to analyze the variance and the importance of customer value more effectively compared with the crisp values. Furthermore, this paper provides the information spread between crisp values and fuzzy values with different consumers' clusters. The information will make it easier for the retailers to prioritize the customer requirements for customer-oriented service.