A fuzzy clustering approach for determination of ideal points of new products
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...
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| Format: | Conference Paper |
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IEEE
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/7199 |
| _version_ | 1848745299073302528 |
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| author | Chan, Kit Yan |
| author2 | IEEE Computational Intelligence Society |
| author_facet | IEEE Computational Intelligence Society Chan, Kit Yan |
| author_sort | Chan, Kit Yan |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T06:15:09Z |
| format | Conference Paper |
| id | curtin-20.500.11937-7199 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:15:09Z |
| publishDate | 2013 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-71992017-09-13T14:38:34Z A fuzzy clustering approach for determination of ideal points of new products Chan, Kit Yan IEEE Computational Intelligence Society Ideal points fuzzy clustering new product development fuzzy data 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. 2013 Conference Paper http://hdl.handle.net/20.500.11937/7199 10.1109/CISIS.2013.25 IEEE fulltext |
| spellingShingle | Ideal points fuzzy clustering new product development fuzzy data Chan, Kit Yan A fuzzy clustering approach for determination of ideal points of new products |
| title | A fuzzy clustering approach for determination of ideal points of new products |
| title_full | A fuzzy clustering approach for determination of ideal points of new products |
| title_fullStr | A fuzzy clustering approach for determination of ideal points of new products |
| title_full_unstemmed | A fuzzy clustering approach for determination of ideal points of new products |
| title_short | A fuzzy clustering approach for determination of ideal points of new products |
| title_sort | fuzzy clustering approach for determination of ideal points of new products |
| topic | Ideal points fuzzy clustering new product development fuzzy data |
| url | http://hdl.handle.net/20.500.11937/7199 |