A THURSTONE-COOMBS MODEL OF CONCURRENT RATINGS WITH SENSORY AND LIKING DIMENSIONS

A popular product testing procedure is to obtain sensory intensity and liking ratings from the same consumers. Consumers are instructed to attend to the sensory attribute, such as sweetness, when generating their liking response. We propose a new model of this concurrent ratings task that conjoins a unidimensional Thurstonian model of the ratings on the sensory dimension with a probabilistic version of Coombs' (1964) unfolding model for the liking dimension. The model assumes that the sensory characteristic of the product has a normal distribution over consumers. An individual consumer selects a sensory rating by comparing the perceived value on the sensory dimension to a set of criteria that partitions the axis into intervals. Each value on the rating scale is associated with a unique interval. To rate liking, the consumer imagines an ideal product, then computes the discrepancy or distance between the product as perceived by the consumer and this imagined ideal. A set of criteria are constructed on this discrepancy dimension that partition the axis into intervals. Each interval is associated with a unique liking rating. The ideal product is assumed to have a univariate normal distribution over consumers on the sensory attribute evaluated. The model is shown to account for 94.2% of the variance in a set of sample data and to fit this data significantly better than a bivariate normal model of the data (concurrent ratings, Thurstonian scaling, Coombs' unfolding model, sensory and liking ratings).