초록/요약

For successful product development and marketing in the food/beverage industry, it is vital to study the product attributes perceived by consumers effectively and efficiently. Recently, a two-step rating-based ‘double-faced applicability’ (DFA) test was developed to study consumer perception and evaluation of product attributes in a quantitative way using d-prime affect magnitude (d'A) based on signal detection theory. This study assessed the product discrimination and characterization performance and interpretationability of d'Aoutput measures of the DFA approach in comparison with the check-all-that-apply (CATA) question. An independent samples design (each N = 108) was used to evaluate eighteen ready-to-drink (RTD) latte products with eighteen attributes. A cluster analysis was also performed, and based on this the relationships of the two output statistics - d'A and total citation frequency were examined. Product attributes were generated based on literature reviews on coffee sensory and emotion studies and sensory/consumer research methodology to encompass consumer perception generally applicable to beverage, and for each attribute, a pair of ‘double-faced’ descriptors in three categories - ‘general weak-strong’, ‘sensory’, and ‘sentimental consequence’ were used for the DFA test. The d'A of the DFA test provided similar product characterization to citation frequency of the CATA question, yet provided better product discrimination and reflected the consumer affective perception for each product independently in a better interpretable way, in valence. It showed a sigmoid relationship with the citation frequency due to its nature of reflecting valence. Overall, the results contribute support for the usefulness of the DFA approach for consumer product testing and suggest the potential of developing a generally applicable DFA test format for studying integrated attribute perception. © 2022 Elsevier Ltd