Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10541
Title: A methodology of generating customer satisfaction models for new product development using a neuro-fuzzy approach
Authors: Kwong, CK 
Wong, TC
Chan, KY
Keywords: Customer satisfaction models
Neuro-fuzzy
New product development
Issue Date: 2009
Publisher: Pergamon Press
Source: Expert systems with applications, 2009, v. 36, no. 8, p. 11262-11270 How to cite?
Journal: Expert systems with applications 
Abstract: When developing new products it is important for design teams to understand customer perceptions of consumer products because the success of such products is heavily dependent upon the associated customer satisfaction level. The chance of a new product's success in a marketplace is higher if users are satisfied with it. In this study, a new methodology of generating customer satisfaction models using a neuro-fuzzy approach is proposed. In contrast to previous research, non-linear and explicit customer satisfaction models can be developed with the use of the proposed methodology. An example of notebook computer design is used to illustrate the methodology. The proposed methodology was measured against the benchmark of statistical regression to determine its effectiveness. Experimental results suggested that the proposed approach outperformed the statistical regression method in terms of mean absolute errors and variance of errors.
URI: http://hdl.handle.net/10397/10541
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2009.02.094
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