A new fuzzy decision-making approach for selecting new product development project

被引:6
|
作者
Wei, Chiu-Chi [1 ]
Andria, Agus [2 ]
Xiao, Houn-Wen [3 ]
Wei, Chiou-Shuei [4 ]
Lai, Ting-Chang [5 ]
机构
[1] Chung Hua Univ, Dept Ind Management, Hsinchu, Taiwan
[2] Chung Hua Univ, PhD Program Technol Management, Hsinchu, Taiwan
[3] Minghsin Univ Sci & Technol, Dept Mkt & Logist Management, Hsinchu, Taiwan
[4] Lunghwa Univ Sci & Technol, Dept Ind Management, Taoyuan, Taiwan
[5] Hsuan Chuang Univ, Dept Business Adm, 48 Hsuan Chuang Rd, Hsinchu 300, Taiwan
来源
关键词
new product development; fuzzy front end; fuzzy set; multi-criteria group decision making; project selection; STRATEGIC PORTFOLIO MANAGEMENT; WEIGHTED-AVERAGE; SUPPORT-SYSTEM; FRONT-END; ENVIRONMENT; CONSENSUS; MODEL;
D O I
10.1177/1063293X16644950
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The most crucial factor that survives enterprises under stiff competition is the success of new product development project; thus, the new product development project selection has become the vital concerns of R&D managers. The initial stage of the project is filled with uncertainties and complexities, which significantly deteriorate the success of product development and product launch. Previous researches focus on helping enterprises determine a set of good product ideas; however, when proceeding to the product development stage after the fuzzy front end, a best product idea should be selected to form a new product development project to create anticipated profits and develop competitive advantage. Therefore, this study proposes a potential project selection model, which combines optimal aggregation method and effective fuzzy weighted average to assist decision maker to achieve the best consistency of fuzzy judgments, and generates a single synergistic index project fuzzy synthetic rating that considers both risk and performance. The project fuzzy synthetic rating index is then used to help make the project Go-Kill decision, and the remaining survival projects are next prioritized to filter the best project. This model can efficiently assist R&D managers in dealing with both uncertainties and complexities when making new product development project screening decision and can reduce decision bias and produce new product development project with the highest possibility of generating expected profit.
引用
收藏
页码:240 / 250
页数:11
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