Title :
A Stepwise-Based Fuzzy Regression Procedure for Developing Customer Preference Models in New Product Development
Author :
Kit Yan Chan ; Hak Keung Lam ; Dillon, Tharam S. ; Sai Ho Ling
Author_Institution :
Dept. of Electr. & Comput. Eng., Curtin Univ., Perth, WA, Australia
Abstract :
Fuzzy regression methods have commonly been used to develop consumer preferences models, which correlate the engineering characteristics with consumer preferences regarding a new product; the consumer preference models provide a platform, whereby product developers can decide the engineering characteristics in order to satisfy consumer preferences prior to developing the products. Recent research shows that these fuzzy regression methods are commonly used to model customer preferences. However, these approaches have a common limitation in that they do not investigate the appropriate polynomial structure, which includes significant regressors with only significant engineering characteristics; also, they cannot generate interaction or high-order regressors in the models. The inclusion of insignificant regressors is not an effective approach when developing the models. Exclusion of significant regressors may affect the generalization capability of the consumer preference models. In this paper, a novel fuzzy modeling method is proposed, namely fuzzy stepwise regression (F-SR), in order to develop a customer preference model which is structured with an appropriate polynomial, which includes only significant regressors. Based on the appropriate polynomial structure, the fuzzy coefficients are determined using the fuzzy least-squares regression. The developed fuzzy regression model attempts to obtain a better generalization capability using a smaller number of regressors. The effectiveness of the F-SR is evaluated based on two design problems, namely a tea maker design and a solder paste dispenser design. Results show that better generalization capabilities can be obtained compared with the fuzzy regression methods commonly used for new product development. In addition, smaller scale consumer preference models with fewer engineering characteristics can be obtained. Hence, a simpler and more effective product development platform can be provided.
Keywords :
consumer behaviour; customer satisfaction; customer services; fuzzy set theory; least squares approximations; product development; regression analysis; F-SR; consumer preference model; consumer preferences model; customer preference model; engineering characteristics; fuzzy least-squares regression; fuzzy modeling method; fuzzy regression method; fuzzy stepwise regression; generalization capability; high-order regressor; new product development; polynomial structure; product developer; solder paste dispenser design; stepwise-based fuzzy regression procedure; Analytical models; Computational modeling; Indexes; Numerical models; Planning; Polynomials; Product development; Consumer preferences; consumer preferences; customer satisfaction; engineering characteristics; fuzzy least square regression; fuzzy least-squares regression; fuzzy regression; new product development; stepwise regression;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2014.2375911