A clustering approach to affective response dimension selection for product design

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

Research output: Contribution to journalArticlepeer-review

24 Citations (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.

Original languageEnglish
Pages (from-to)197-206
Number of pages10
JournalJournal of Convergence Information Technology
Issue number2
Publication statusPublished - 2011 Feb 1

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications


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