Paper Info
Title
A fuzzy ordinary regression method for modeling customer preference in tea maker design
Abstract
Faced with fierce competition in marketplaces, manufacturers need to determine the appropriate settings of engineering characteristics of the new products so that the best customer preferences of the products can be obtained. To achieve this, functional models relating customer preferences to engineering characteristics need to be developed. As information regarding functional relationships between customer preferences are generally subjective or heuristic in nature, development of the customer preference models involve two uncertainties, namely fuzziness and randomness. Existing approaches use only fuzzy-based technologies to address the uncertainty caused by fuzziness. They are not designed to address the randomness of the observed data which is caused by a limited knowledge of the variability of influences between customer preferences and engineering characteristics. In this article, a fuzzy ordinary regression method is proposed to develop the customer preference models which are capable of addressing the two uncertainties of crispness and fuzziness of the customer preferences. A case study of a tea maker design which involves both uncertainties is used to demonstrate the effectiveness of the proposed method.
Year
DOI
Venue
2014
10.1016/j.neucom.2013.12.056
Neurocomputing
Keywords
Field
DocType
tea makers,customer preference,fuzzy modeling,new product development,fuzzy regression
Customer preference,Voice of the customer,Artificial intelligence,Management science,Randomness,New product development,Customer intelligence,Heuristic,Regression,Fuzzy logic,Operations research,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
142
1
0925-2312
Citations 
PageRank 
References 
6
0.50
10
Authors
3
Name
Order
Citations
PageRank
Kit Yan Chan147045.36
C. K. Kwong253340.00
M. C. Law360.50