文献类型：期刊文献

英文题名：Research on the design method of extracting optimal kansei vocabulary

作者：Kang, Xinhui[1]; Yang, Minggang[1]; Wu, Yixiang[1]; Yuan, Haozhou[1]

机构：[1] School of Art, Design and Media, East China University of Science and Technology, No. 130 Meilong Road, Xuhui District, Shanghai, 200237, China

年份：2017

卷号：10273 LNCS

起止页码：194

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20173003975894)

语种：英文

外文关键词：Semantics - Product design - Sales

摘要：In the relevant researches on Kansei Engineering, the Kansei Vocabulary extraction has a vital significance. In previous time, the Kansei words are selected by experts’ focus interviews or customers’ giving marks. Such kind of method is easy, but it is difficult to explore the customers’ inner feeling, which seems to be so hasty. In this research, a method of selecting optimal Kansei Vocabulary is proposed to assist the designers establish the high correlation degree’s emotion cognition of customers. The factor analysis is used to classify the Kansei semantic style. Using the Fuzzy Analytic Hierarchy Process to make comparisons of each two specific Kansei words can get the final weight order. Through this method in the minicar’s case study, the modern factors’ "concise", "smooth" words are defined as the words which can most arouse the customers’ emotional resonance. The research proves that the design method of extracting the optimal Kansei Vocabulary is the most effective one. Meanwhile, it can be applied into the modeling design of other industrial products. ? Springer International Publishing AG 2017.