A proportional 3-tuple fuzzy linguistic representation model for screening new product projects

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• 作者：Wen-Tao Guo ; Van-Nam Huynh…
• 关键词：Confidence levels ; ignoring information ; linguistic modeling ; proportional 3 ; tuple ; screening new product projects
• 刊名：Journal of Systems Science and Systems Engineering
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：25
• 期：1
• 页码：1-22
• 全文大小：975 KB
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• 作者单位：Wen-Tao Guo (1)
  Van-Nam Huynh (1)
  Yoshiteru Nakamori (1)
  
  1. School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292, Japan
  
• 刊物类别：Engineering
• 刊物主题：Systems and Information Theory in Engineering
  Game Theory and Mathematical Methods
  Operation Research and Decision Theory
  Chinese Library of Science
  
• 出版者：Systems Engineering Society of China, co-published with Springer-Verlag GmbH
• ISSN：1861-9576

文摘

It is critically important for companies to screen new product projects before they are launched to the market. So far, many approaches have been developed for tackling the process of screening product innovations. Due to uncertain, vague and incomplete information as well as dynamically complex process regarding to new product development (NPD), a fuzzy linguistic approach employed linguistic assessments and the fuzzy-set-based computation is reasonable for screening new products. However, such a fuzzy linguistic approach faces with various defects and limitations, such as loss of information, failing in considering the aspects related to human nature on uncertain subjective judgments etc. These defects and limitations lead to a dilemma, i.e., it’s very difficult to screen new product projects reasonably and precisely. In this paper, we propose a notion of proportional 3-tuple to represent a linguistic assessment and related ignoring information, and a preference-preserving proportional 3-tuple transformation for the unification of linguistic assessments represented by proportional 3-tuples between two different linguistic term sets. On this basis, a proportional 3-tuple fuzzy linguistic representation model for screening new product projects is developed. It is shown that the proposed model is flexible to handle uncertain, vague and incomplete information related to screening new product projects. It not only allows evaluators to express their subjective judgments with different confidence levels, but is also able to deal with incomplete linguistic assessments. Ultimately, the proposed model also improves the precision and reasonability of the screening result.