Developing a reduced consumer-led lexicon to measure emotional response to beer
By Carolina Chaya, Curtis Eaton, L. Hewson, Rocío Fernández Vázquez, V. Fernández-Ruíz, K. Smart, J. Hort. 2015
89 citations recorded by the source corpus.
Abstract Previous researchers have recently recommended and utilised consumer-led lexicons to measure emotional response. This study further advances this approach by (1) making the lexicon generation process more efficient by using consumer focus groups as opposed to individual consumer interviews and (2) decreasing the number of responses required from each consumer by reducing the lexicon to categories of similar terms. In response to 10 lager samples which were manipulated in order to control selected sensory properties, focus groups generated a lexicon of 44 emotion terms. This lexicon was reduced to 12 distinct emotion categories using linguistic checks and cluster analysis. Naive beer consumers ( n = 113) used these 12 emotion categories to rate their emotional response to the 10 samples. The reduced consumer-led lexicon was validated through its ability to discriminate across samples as well as show differences in emotional response between genders and age groups. The 12 emotion categories were found to discriminate well between samples, although a number of categories grouped samples similarly. However, differences in responses to otherwise comparable emotion categories were identified between genders and age groups, highlighting the importance of including all emotion categories so as to not over-reduce the lexicon and risk missing out on valuable emotion data.
Subfields: Food Science, Tourism, Leisure and Hospitality Management
View Paper: https://www.semanticscholar.org/paper/f7dcbaa04909dc959af57f5d4752c338e76a0525
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Citations in the corpus
- Product uniqueness: Further exploration and application of a consumer-based methodology (2017, background): “It is clear that consumers’ emotional responses to products are an important measure by which to differentiate among them (Chaya et al., 2015), and to characterize them in terms of important drivers of purchase and choice.”