A study on extraction of consumer affective factor for Kansei engineering

Abstract The study of Consumer Affective Factor (CAF) for Kansei engineering has been an important issue in the industrial design field in recent years. CAF is usually presented in the form of adjectives. Based on the Kansei Engineering (KE) concept, this study conducted Factor Analysis (FA) and Procuresses Analysis (PA) to select the CAF from digital camera product's shape. First, in the initial stage of the study, 120 samples of digital camera were col- lected from the fashion market place in Taiwan. In the meanwhile, we deleted more similar appearance digital camera samples to obtain 50 samples for experiment. Twenty pairs of ad- jectives describing the digital cameras were used for a Semantic Differential (SD) experiment. The results of the factor loaded from the FA, then we could obtain representative pairs of adjectives. PA was also used to decide adjective priorities according to the sorting rule. Final results showed that the PA was an effective method for the CAF selection.

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