Comparing a full and reduced version of a consumer‐led lexicon to measure emotional response to beer

Abstract

Verbal self‐report emotion measures in sensory and consumer science commonly include a long lexicon of terms with an associated potential for participant boredom and fatigue. This study assessed the effectiveness of reducing the number of terms in a product‐specific lexicon by comparing a reduced form to a full form. The relative abilities of each lexicon to discriminate between beer samples were evaluated. Focus groups of UK beer consumers generated 43 emotion terms in response to a set of sensorially distinct lager samples. These terms were used by the participants to individually rate their emotional responses to lager samples. Cluster analysis, modified via linguistic checks, was used to group terms by similarity into emotion categories. Nine categories were defined which became the reduced lexicon. Subsequently, naïve beer consumers (n = 109) rated their emotional responses to the samples using both the full and reduced lexicons. The emotional spaces generated by both lexicons were comparable, although there were relative gains and losses in discrimination associated with each. However, overall, the forms were consistent in sample discriminability and use of the reduced emotion form was concluded to be preferable for product comparisons because of the significant savings in both time and resources. Practical applications Emotion measurement has been previously shown to go beyond hedonic measures in product discrimination. The present research has shown that, in commercial environments, a reduced product‐specific emotion lexicon may be preferable to a full version given the similarity between form lengths for sample discriminability in addition to significant savings in both time and resources.

Comparison of methods to develop an emotional lexicon of wine: Conventional vs rapid-method approach

“…Similar results were reported by Mora et al (2018) and were consistent with the first dimension of the circumplex model of emotions (Larsen & Diener, 1992;Russel, 1980;Watson & Tellegen, 1985). However, the second dimension of the present study (PC2) did not follow the theoretical model of previous literature and reported in other studies, in which a clearer relationship between PC2 and activation/arousal was evidenced for wine (Mora et al, 2018), blackcurrant squashes (Ng et al, 2013), beer (Chaya et al, 2015;Eaton et al, 2019, Mora et al, 2019, and coffee (Bhumiratana et al, 2014). Apparently, results from this research showed that the emotions associated with low or high activation were not so related to PC2 but were more combined with the valence axis (PC1).…”

“…For example, Chaya et al (2015) applied Hierarchical Cluster Analysis (HCA) to group terms with similar ratings into emotional categories, and to reduce the length of the questionnaire. The effectiveness of this approach was analyzed by Eaton, Chaya, Smart, and Hort (2019). Considering all these factors, when the emotional response elicited by food is assessed, specific "shorter/easier" questionnaires or methods belonging to the consumers' culture must be applied.…”

“…Then, in some cases, additional consumer tests are carried out to rate the emotions elicited by several products with different sensory properties using the emotional terms previously developed. Hierarchical Cluster Analysis is used to group the different emotions into emotional categories; this step may need to be supervised by the research team (Chaya et al, 2015;Eaton et al, 2019;Mora et al, 2019). Finally, the resulting lexicon has to be tested to confirm its ability to measure the emotional response evoked by the specific product.…”

The effect of consumption context on consumer hedonics, emotional response and beer choice

“…Data was collected using an online questionnaire via Compusense Cloud (Version 8.0.6288.23054, Compusense Inc., Guelph, Ontario, Canada). Participant's emotional response to each product was measured directly after tasting the beer using a previously developed beer specific emotion lexicon (Dorado et al, 2016;Eaton, Chaya, Smart, & Hort, 2018) consisting of ten emotion categories (Table 1). Each of the ten emotion categories was presented together with the associated terms and participants were asked to indicate the extent to which they were experiencing the emotions associated with those descriptors by giving an intensity rating on continuous line scale anchored from 'very low' to 'very high' at 5% and 95% of the scale.…”

New Digital Infrastructure, Cross-Border E-Commerce and Global Vision of Creating Electronic World Trade Platform

“…During each session, participants reported their emotional response and liking for the beer (I) after the first sip, (II) after consuming half of the beer in the glass (approximately 142 ml) and (III) after consuming all of the beer in the glass (approximately 284 ml). A reduced beer specific emotion lexicon (Eaton, Chaya, Smart, & Hort, 2019) was used to determine emotional response at each consumption stage. The emotion terms for each category were presented together and participants were asked to rate each category on ten separate continuous line-scales of which the ends were labelled from 'very low' to 'very high' at 5% and 95% of the scale.…”