A new integrated fuzzy QFD approach for market segments evaluation and selection

NCUIR > School of Management at National Central University > Graduate Institute of Industrial Management > journal & Dissertation > Item 987654321/99942

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Title:	A new integrated fuzzy QFD approach for market segments evaluation and selection
Authors:	高信培;Dat, Luu Quoc;Phuong, Thinh Thi;Kao, Hsing-Pei;Chou, Shuo-Yan;Nghia, Pham Van
Contributors:	管理學院工業管理研究所
Keywords:	Fuzzy QFD;Fuzzy TOPSIS;Market segment selection
Date:	2015-01-01
Issue Date:	2026-04-21 13:42:23 (UTC+8)
Publisher:	Elsevier Inc.;Elsevier Inc
Abstract:	摘要： 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. Finally, this paper compares the proposed approach with another fuzzy QFD approach, demonstrating the advantages of the proposed approach. 出版者： Elsevier Inc 出版日期： 2015-07-01 出處： Applied mathematical modelling, 2015-07, Vol.39 (13), p.3653-3665 資源來源： Elsevier ScienceDirect Journals Complete 版權： 2015 Elsevier Inc. 識別號： ISSN: 0307-904X 識別號： DOI: 10.1016/j.apm.2014.11.051
Appears in Collections:	[Graduate Institute of Industrial Management] journal & Dissertation

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