Title
A new fuzzy decision-making approach for selecting new product development project.
Abstract
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.
Year
DOI
Venue
2016
10.1177/1063293X16644950
CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS
Keywords
Field
DocType
new product development,fuzzy front end,fuzzy set,multi-criteria group decision making,project selection
Front and back ends,Systems engineering,Fuzzy logic,Competitive advantage,Fuzzy set,Project selection,Engineering,Fuzzy decision,Management science,Profit (economics),New product development
Journal
Volume
Issue
ISSN
24.0
3.0
1063-293X
Citations 
PageRank 
References 
1
0.37
13
Authors
5
Name
Order
Citations
PageRank
Chiu-Chi Wei1326.90
Agus Andria210.71
Houn-Wen Xiao310.37
Chiou Shuei Wei441.50
Ting-Chang Lai510.37