Theme-Based Comprehensive Evaluation in New Product Development Using Fuzzy Hierarchical Criteria Group Decision-Making Method

被引:55
|
作者
Lu, Jie [1 ]
Ma, Jun [1 ]
Zhang, Guangquan [1 ]
Zhu, Yijun [2 ]
Zeng, Xianyi [3 ]
Koehl, Ludovic [3 ]
机构
[1] Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Quantum Computat & Intelligent Syst, Decis Syst & E Serv Intelligence Lab, Sydney, NSW 2007, Australia
[2] Univ Sci & Technol Lille, F-59650 Villeneuve Dascq, France
[3] Ecole Natl Super Arts & Ind Text, French Engineer Sch, F-59100 Roubaix, France
基金
澳大利亚研究理事会;
关键词
Decision support systems; digital ecosystems; fuzzy sets; multicriteria decision making (MCDM); new product development (NPD); product evaluation; INDUCTION-MOTOR; SELECTION; SYSTEMS; FUSION;
D O I
10.1109/TIE.2010.2096171
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
One of the features of the digital ecosystem is the integration of human cognition and socio-economic themes into the process of new product development (NPD). In a socio-economic theme-based NPD, ranking a set of product prototypes that have been designed always requires the participation of multiple evaluators and consideration of multiple evaluation criteria. Using the well-being theme-based garment NPD as a background, this paper first presents a fuzzy hierarchical criteria group decision-making (FHCGDM) method which can effectively calculate final ranking results through fusing all assessment data from human beings and machines. It then presents a garment NPD comprehensive evaluation model with hierarchical criteria under the well-being theme through identifying a set of marketing tactics from a consumer acceptance survey. It further provides an establishment process for an NPD evaluation model under the digital ecosystem framework. Finally, a garment NPD case study further demonstrates the proposed well-being NPD comprehensive evaluation model and the FHCGDM method. The advantages of the proposed evaluation method include successfully handling criteria in a hierarchical structure, automatically processing both objective measurements from machines and subjective assessments from human evaluators, and using the most suitable type of fuzzy numbers to describe linguistic terms.
引用
收藏
页码:2236 / 2246
页数:11
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