9. Glossary
Principal component analysis (PCA)
Principal component analysis (PCA) is a method of statistical data analysis that reduces the number of initial variables by retaining only the main components or axes. Reduction to these independent axes enables data variability to be better explained and interpreted.
ANOVA
ANOVA is a statistical approach that highlights the variance observed in a variable as a function of other so-called explanatory variables. It is referred to as a one-factor or multifactor analysis, depending on the number of variability factors.
Emotional descriptor
Emotional descriptors are adjectives that characterize the consumer's reaction to a product-service stimulus. This reaction is situated on three axes of intensity (strong,...
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BOUCHARD C., MANTELET F., AOUSSAT A., SOLVES C., GONZALEZ J. C., PEARCE K., COLEMAN S. (2009), A European emotional investigation in the field of shoes design , International Journal of Product Development, Volume 7, Issue 1-2, 2009, pp. 3-27
PLUTCHIK R., The nature of emotions , America, Scientist, Volume 89, 2001, July-August
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In the "search" box, enter the word Kansei and launch the query. The article presents an exhibition devoted to Japanese design organized in 2008 by the Arts Décoratifs to illustrate the quality and innovation of contemporary Japanese design. Kansei or sensibility here refers to "a sense of hospitality, a vision of nature nourished by...
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