Comparison of response formats and concurrent hedonic measures for optimal use of the EmoSensory® Wheel

Research output: Contribution to journalJournal articleResearchpeer-review

Joachim J. Schouteten, Xavier Gellynck, Ilse De Bourdeaudhuij, Benedikt Sas, Wender Bredie, Armando Perez-Cueto, Hans De Steur

The study of emotional and sensory profiling with food products is gaining momentum in the field of sensory research. These methods can be applied in order to obtain a broader consumer perspective on product performance beyond traditional hedonic measurements (Jiang, King, & Prinyawiwatkul, 2014; Varela & Ares, 2012). The EmoSensory® Wheel, a recently introduced method which combines emotional and sensory assessment in a wheel questionnaire format is one example of conducting such a task in a consumer-friendly way. However, little is known about its performance compared to a traditional list-based questionnaire format. This comparison is undertaken in this study for two product categories (chocolate and yogurt). Further, two methodological issues are addressed by (i) comparing the use of Check-All-That-Apply (CATA) and rate-all-that-apply (RATA) response formats and (ii) examining whether the method impacts on the concurrent hedonic product assessment for two product categories (chocolate and yogurt). Although both questionnaire formats showed similar findings, more consumers preferred the wheel questionnaire format. Regarding the latter, CATA and RATA scaling yielded similar performance and no influence on the concurrent hedonic assessment was found. This study lends further support for combining emotional and sensory measurements using the EmoSensory® profile, which is of interest for food scientists and the food industry.

Original languageEnglish
JournalFood Research International
Volume93
Pages (from-to)33-42
Number of pages10
ISSN0963-9969
DOIs
Publication statusPublished - 2017

    Research areas

  • Attribute scaling, Check-All-That-Apply (CATA), Consumer research, Emotion, Hedonic bias, Rate-All-That-Apply (RATA)

ID: 172885193