• 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