Derived attributes as mediators between categorization and acceptance of a new functional drink

Previous research has given inconsistent results about how categorization influences hedonic ratings. This study used social representation theory to explore the role of categorization, derived attributes, and degree of liking in predicting acceptance, measured as post-exposure liking and preferred frequency to use a new functional drink. Two categories, “technological” and “natural”, were offered as verbal–visual information, characterizing opposite themata of social representation of new foods, in a between-subjects design with 62 women. The women were assigned into two groups, respectively. Liking and preferred frequency to use were rated at two experimental sessions and during a 6-day home use period between them, and 18 derived attributes were rated at the final session. Derived attributes were categorized into four subgroups using principal component analysis. Derived attributes of artificial and regular were predicted by technological or natural category information, respectively, while beneficial and unnecessary were not. The four derived attributes and liking ratings predicted up to 81% of post-exposure liking. The derived attributes predicted up to 11–32% of preferred frequency to use; however, when added to the model, liking ratings replaced their significance, predicting up to 67% of preferred frequency to use. As the groups objectified the product differently depending on the category, it is concluded that the derived attributes had a mediating role between categorization and product acceptance.