DocumentCode :
3113868
Title :
A Fuzzy Clustering Approach for Determination of Ideal Points of New Products
Author :
Kit Yan Chan
Author_Institution :
Dept. of Electr. & Comput. Eng., Curtin Univ., Perth, WA, Australia
fYear :
2013
fDate :
3-5 July 2013
Firstpage :
99
Lastpage :
103
Abstract :
Prior to manufacture a new products, consumers with similar purchasing attitudes are grouped into clusters of which their central points are used as ideal points for new product development. However, many clustering methods ignore the fuzziness of consumers in purchasing products or conducing survey. This paper presents a new method which integrates a fuzzy data processing technique for dimension reduction of customer attributes and a fuzzy clustering technique for grouping consumers with similar purchasing attributes. Hence, the central points of each group are treated as the ideal points for new product development. The effectiveness of the proposed method is demonstrated based on a new product design problem for new digital cameras.
Keywords :
fuzzy set theory; pattern clustering; product design; product development; purchasing; central points; customer attributes; digital cameras; dimension reduction; fuzzy clustering approach; fuzzy data processing technique; ideal point determination; product design problem; product development; purchasing attributes; Clustering methods; Data processing; Digital cameras; Neural networks; Principal component analysis; Product design; Product development; Ideal points; fuzzy clustering; fuzzy data; new product development;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complex, Intelligent, and Software Intensive Systems (CISIS), 2013 Seventh International Conference on
Conference_Location :
Taichung
Print_ISBN :
978-0-7695-4992-7
Type :
conf
DOI :
10.1109/CISIS.2013.25
Filename :
6603873
Link To Document :
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