详细信息

Integrating rough set theory with customer satisfaction to construct a novel approach for mining product design rules  ( SCI-EXPANDED收录 EI收录)  

文献类型:期刊文献

英文题名:Integrating rough set theory with customer satisfaction to construct a novel approach for mining product design rules

作者:Wang, Tianxiong[1];Zhou, Meiyu[1]

机构:[1]East China Univ Sci & Technol, Sch Art Design & Media, 130 Meilong Rd, Shanghai 200237, Peoples R China

年份:2021

卷号:41

期号:1

起止页码:331

外文期刊名:JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

收录:;EI(收录号:20213410805847);WOS:【SSCI(收录号:WOS:000685896700021),SCI-EXPANDED(收录号:WOS:000685896700021)】;

语种:英文

外文关键词:Rough set; semantic difference method; fuzzy set; customer satisfaction; kansei engineering

摘要:When users choose a product, they consider the emotional experience triggered by the product form. In view of the fact that traditional kansei engineering can not effectively reflect the complex and changeable psychological factors of users, and it has not explored the complex relationship between customer satisfaction and perceptual demand characteristics. To address this problem, some uncertainty techniques including rough sets and fuzzy sets are applied to capture more accurate emotion knowledge. Therefore, this research proposes an integrated evaluation gird method (EGM), rough set theory (RST), continuous fuzzy kano model (CFKM), fuzzy weighted association rule mining method to extract the significant relationship between user needs and product morphological features. The EGM is applied to analyze the attractive factor of morphological characteristics of the product, and then the demand items with the highest satisfaction are analyzed through CFKM. The semantic difference method is combined to construct a decision table, and through attribute reduction and importance calculation to obtain the weight of the core product design items. In order to explore the non-linear relationship between design elements and kansei images, the fuzzy weighted association rule mining method was applied to obtain the set of frequent fuzzy weighted association rules based on evidence theory's reliability indices of minimum support and confidence so as to realize user demand-driven product design. Taking the design of electric bicycle as an example, the experiment results show that the proposed method can help companies or designers develop products to generate good solutions for customer need.

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