A fuzzy clustering approach for determination of ideal points of new products
|dc.contributor.author||Chan, Kit Yan|
|dc.contributor.editor||IEEE Computational Intelligence Society|
|dc.identifier.citation||Chan, Kit Yan. 2013. A fuzzy clustering approach for determination of ideal points of new products, in IEEE Computational Intelligence Society (ed), The 7th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS), Jul 3-5 2013, pp. 99-103. Taichung, Taiwan: IEEE.|
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.
|dc.subject||new product development|
|dc.title||A fuzzy clustering approach for determination of ideal points of new products|
|dcterms.source.title||Proceedings of the The 7th International Conference on Complex, Intelligent, and Software Intensive Systeme|
|dcterms.source.series||Proceedings of the The 7th International Conference on Complex, Intelligent, and Software Intensive Systeme|
|dcterms.source.conference||The 7th International Conference on Complex, Intelligent, and Software Intensive Systeme|
|dcterms.source.conference-start-date||Jul 3 2013|
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