TAILIEUCHUNG - A new integrated fuzzy QFD approach for market segments evaluation and selection
This study proposes a new integrated fuzzy quality function deployment (QFD) to support the market segment selection and evaluation process. The proposed approach identifies the features that the market segments should have (‘‘WHATs’’), in order to fit with the company’s business strengths (‘‘HOWs’’). | Applied Mathematical Modelling 39 (2015) 3653–3665 Contents lists available at ScienceDirect Applied Mathematical Modelling journal homepage: A new integrated fuzzy QFD approach for market segments evaluation and selection Luu Quoc Dat a,⇑, Thinh Thi Phuong b, Hsing-Pei Kao b, Shuo-Yan Chou c, Pham Van Nghia d a University of Economics and Business, Vietnam National University, 144 Xuan Thuy Rd., Hanoi, Viet Nam Department of Industrial Management, National Central University, 300, Jhongda Road, Jhongli, Taoyuan 32001, Taiwan c Department of Industrial Management, National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei 10607, Taiwan d Thuan Yen JSC, 62 Kim Dong Rd., Hanoi, Viet Nam b a r t i c l e i n f o Article history: Received 4 April 2013 Received in revised form 24 October 2014 Accepted 20 November 2014 Available online 12 December 2014 Keywords: Market segment selection Fuzzy QFD Fuzzy TOPSIS a b s t r a c t Market segment selection and evaluation are critical marketing activities of all companies. To evaluate and select appropriate market segments, several decision makers and criteria must be involved in the decision process. This study proposes a new integrated fuzzy quality function deployment (QFD) to support the market segment selection and evaluation process. The proposed approach identifies the features that the market segments should have (‘‘WHATs’’), in order to fit with the company’s business strengths (‘‘HOWs’’). In the proposed approach, the relative importance of the ‘‘WHATs’’, the ‘‘HOWs’’–‘‘WHATs’’ correlation scores, the resulting weights of the ‘‘HOWs’’, and the impact of each potential market segment, are assessed in linguistic values. The functions of the averaged ratings and averaged weights are then defined, and fuzzy TOPSIS is used to obtain the final ranking of alternatives. The computational procedure of the proposed approach is further illustrated through a case study.
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