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標題Title: Selecting representative affective dimensions using Procrustes analysis
作者Authors: 楊智傑,Meng-Dar..等
上傳單位Department: 多媒體與電腦娛樂科學系
上傳時間Date: 2009-11-16
上傳者Author: 楊智傑
審核單位Department: 多媒體與電腦娛樂科學系
審核老師Teacher: 楊智傑
檔案類型Categories: 論文Thesis
關鍵詞Keyword: Factor analysis, Cluster analysis, Procrustes analysis, Kansei engineering; Product design
摘要Abstract: Collecting affective responses (ARs) from consumers is of crucial importance to designers wishing to produce an appealing product. Adjectives are often used by researchers as an affective means for consumers to describe their subjective feelings about a given product design. This study proposes a Kansei engineering (KE) approach to select representative affective dimensions using factor analysis (FA) and Procrustes analysis (PA). A semantic differential (SD) experiment asks consumers their ARs toward a set of representative product samples. FA is used to extract underlying latent factors using an initial set of affective dimensions. A backward elimination process based on PA is capable of determining the relative importance of adjectives in each step according to the calculated residual sum of squared differences (RSSDs). Finally, the ranking of the initial set of adjectives is obtained. A case study of mobile phone design is given to demonstrate the analysis results.

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