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Predicting consumer liking and preference based on emotional responses and sensory perception: A study with basic
Shilpa S Samant1, Matthew J Chapko1, Han-Seok Seo1
1Department of Food Science, University of Arkansas, 2650 North Young Avenue, Fayetteville, AR 72704, USA.
Food Research International (Ottawa, Ont.)
|September 7, 2017
Summary
Understanding consumer liking and preference for foods involves measuring emotions alongside sensory perceptions. This study found that emotions, particularly self-reported and facial expressions, combined with taste intensity, best predict overall liking and preference.
Area of Science:
- Food science and sensory analysis
- Consumer behavior research
- Psychology and affective science
Background:
- Traditional sensory testing often overlooks emotional responses to food and beverages.
- Understanding the interplay between sensory perception, emotion, and consumer choice is crucial for product development.
- Existing models may not fully capture the complexity of consumer acceptance.
Purpose of the Study:
- To develop a predictive model for overall liking (rating) and preference (choice) of food and beverages.
- To investigate the role of evoked emotions, alongside taste intensity, in predicting consumer acceptance.
- To compare the effectiveness of different emotion measurement methods (self-report, facial expression, autonomic nervous system responses).
Main Methods:
- 102 participants tasted and rated basic taste solutions (water, sucrose, citric acid, salt, caffeine).
- Emotional responses were measured using the EsSense25 questionnaire, facial expression analysis, and autonomic nervous system (ANS) responses.
- Perceived taste intensity, overall liking, and preference rankings were recorded.
Main Results:
- Self-reported emotions and facial expression analysis, combined with perceived taste intensity, were the strongest predictors of liking and preference.
- Autonomic nervous system (ANS) measures showed limited predictive value.
- Both positive and negative emotions contributed to predicting consumer liking and preference, challenging some prior research.
- Subtle differences were observed in the prediction models for liking versus preference.
Conclusions:
- A combination of evoked emotions and sensory perception provides a more comprehensive understanding of consumer acceptance and preference.
- Integrating emotional measurement into sensory testing is vital for accurate prediction of consumer behavior.
- Both overall liking and preference are important metrics that require distinct consideration in consumer research.