Deakin University

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Considering the application of a mixed reality context and consumer segmentation when evaluating emotional response to tea break snacks

journal contribution
posted on 2021-03-01, 00:00 authored by Yu Qing Low, Vivian H F Lin, Liang Jun Yeon, Joanne Hort
Emotional response is dependent on context and the individual. Increasingly consumer scientists are collecting emotional response data as it gives deeper insights over liking concerning engagement with food products. This research investigated the impact of context on consumer emotional response to tea-break snacks across different context including the use of mixed-reality. It also aimed to determine if consumers can be segmented according to their patterns of emotional response as opposed to liking. Consumers (n = 120) evaluated two tea-break snacks across three different contexts (sensory booth, evoked mixed-reality café, real life café) using a rate-all-that-apply EsSense 25 questionnaire. Cluster analysis reduced the 25 emotional terms to a more manageable nine categories of emotional response for data analysis. Using those categories, three emotion-based segments of tea-break snack consumers were identified. One emotionally disengaged, and two positively engaged but at different levels of intensity and for different attributes. For most consumers, mixed-reality evoked similar emotional responses and discrimination between the snacks as the real café suggesting it is a useful technique for evaluating ecologically valid consumer response. Responses in the sensory booths were different. This, suggests including context in consumer emotional response data collection is important. Furthermore, this research suggests that researchers should consider including context within consumer testing that involves emotional response and that mixed-reality serves as a promising approach to do this. It also highlights that average consumer emotional responses are unlikely to be representative and that segmenting consumers according to their emotional response will reveal deeper insights into product response.



Food quality and preference



Article number



1 - 14




Amsterdam, The Netherlands







Publication classification

C1 Refereed article in a scholarly journal