Decoding Preferences: A Comparative Analysis of Non-Alcoholic and Alcoholic Cocktails through Acceptance and Qualitative Insights

Abstract

This study aimed to evaluate consumer perception and acceptance of non-alcoholic cocktails compared to their traditional alcoholic counterparts in a restaurant setting. Three popular cocktails—gintonic, mojito, and mule—and their non-alcoholic versions (NoLo) were assessed following a three × two experimental design. A total of 600 participants (approximately 100 per cocktail) participated at the Basque Culinary Center’s restaurant. Participants rated their liking of the cocktails using a nine-point hedonic scale and provided open-ended responses about the sensory characteristics and the consumption contexts or emotions evoked by the different cocktails. The results showed differences in the acceptance of the six cocktails, but no significant differences between the alcoholic and non-alcoholic versions, suggesting that NoLo alternatives were similarly well-received. Open-ended responses were analyzed using latent dirichlet allocation (LDA) to uncover latent topics, and Fisher’s exact test and correspondence analysis were used to identify differences in the mentioned topics per cocktail. Specific sensory attributes, emotions, and contexts were associated with each type of cocktail, but no differences were found between the alcoholic and non-alcoholic versions. These findings demonstrate the viability of non-alcoholic cocktails in real consumption settings, eliciting similar liking scores, sensory attributes, contexts, and emotions in consumers. This study also highlighted the potential of natural language processing techniques for analyzing open-ended questions.

Keywords

• consumer perception
• real context
• natural language processing
• latent dirichlet allocation