Theme-Based Comprehensive Evaluation in New Product Development Using Fuzzy Hierarchical Criteria Group Decision-Making Method
Theme-Based Comprehensive Evaluation in New Product Development Using Fuzzy Hierarchical Criteria Group Decision-Making Method
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DOI：
10.1109/tie.2010.2096171
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发表时间：
2011-06
影响因子：
7.7
通讯作者：
Jie Lu;Jun Ma;Guangquan Zhang;Yijun Zhu;Xianyi Zeng;L. Koehl
中科院分区：
文献类型：
--
作者：
Jie Lu;Jun Ma;Guangquan Zhang;Yijun Zhu;Xianyi Zeng;L. Koehl
数字生态系统的特征之一是将人类认知和社会经济主题整合到新产品开发（NPD）过程中。在基于社会经济主题的新产品开发中，对一组已设计的产品原型进行排序总是需要多个评估者的参与和考虑多个评估标准。以基于健康主题的服装新产品开发为背景，提出了一种模糊层次准则群决策（FHCGDM）方法，该方法通过融合来自人和机器的所有评价数据，有效地计算出最终的排序结果。通过消费者接受度调查，确定了一套营销策略，提出了一个基于幸福感主题的服装新产品开发综合评价模型。并给出了数字生态系统框架下新产品开发评价模型的建立过程。最后，通过服装新产品开发案例进一步验证了所提出的幸福感新产品开发综合评价模型和FHCGDM方法。所提出的评价方法的优点包括成功地处理标准的层次结构，自动处理客观测量从机器和主观评估从人类评估，并使用最合适的类型的模糊数来描述语言术语。
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.