Integrating Kansei engineering with conjoint analysis to fulfil market segmentation and product customisation for digital cameras

Chih-Hsuan Wang

International Journal of Production Research, 2015, vol. 53, issue 8, 2427-2438

Abstract: Diverse customer desires coupled with technological advances have forced companies to manufacture products with ultimate performance, low cost, high quality and much shorter time-to-market. Recently, the popularity of smart phones has given rise to seriously declined product sales of digital cameras. In this paper, a two-phase framework is presented to offer decision supports on developing next-generation cameras. In the phase of market segmentation, Kansei engineering is employed to capture customer perceptions of affective features. Then, rough set theory is conducted to generate decision rules for partitioning the whole market into the consumer segment and the professional segment, respectively. In the phase of product customisation, conjoint analysis is applied to extract customer preferences for functional features. Furthermore, Grey relational analysis is conducted to select the top three varieties with regard to two distinct segments. In particular, this paper is capable to help brand companies or camera manufacturers better capture customer perceptions and preferences for digital cameras, effectively perform market segmentation (based on affective features) and efficiently conduct product customisation (based on functional features).

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2014.974840 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:53:y:2015:i:8:p:2427-2438

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2014.974840

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().