A clustering approach to affective response dimension selection for product design

Meng-Dar Shieh, Tsung Hsing Wang, Chih Chieh Yang

研究成果: Article同行評審

23 引文 斯高帕斯(Scopus)


Consumers' affective responses (CARs) to the appearance of a product will greatly influence their purchasing decisions. In the product design field, researchers often provide adjectives so that consumers can express their subjective feelings. However, there exists both similarity and svagueness among these adjectives, which make it difficult to choose suitable adjectives for semantic differential (SD) experiments. In order to facilitate the task for selecting representative adjectives, which we call" affective response dimension selection (ARDS)", this study proposes an approach based on factor analysis (FA), hierarchical clustering analysis (HCA) and k-means clustering. A case study of mobile phone design is used to demonstrate the effectiveness of the proposed approach. Three representative pair wise adjective, coarse-delicate, unoriginal-creative and discordant-harmonious were obtained from the experimental results conducted on the initial set of 22 pair wise adjectives. This proposed ARDS method is very helpful to product designers during new product development.

頁(從 - 到)197-206
期刊Journal of Convergence Information Technology
出版狀態Published - 2011 2月 1

All Science Journal Classification (ASJC) codes

  • 硬體和架構
  • 電腦網路與通信


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