Just-about-right (JAR) scaling is criticized for measuring attribute intensity and acceptability simultaneously. Using JAR scaling, an attribute is evaluated for its appropriateness relative to one's hypothetical ideal level that is pre-defined at the middle of a continuum. Alternatively, ideal scaling measures these two constructs separately. Ideal scaling allows participants to rate their ideal freely on the scale (i.e., without assuming the "Too Little" and "Too Much" regions are equal in size). We hypothesized that constraining participants' ideal to the center point, as is done in the JAR scale, may cause a scaling bias and, thereby, influence the magnitude of "Too Little" and "Too Much". Furthermore, we hypothesized that the magnitude of "Too Little" and "Too Much" would influence liking to different extents. Coffee-flavored dairy beverages (n=20) were formulated using a fractional, constrained-mixture design that varied the ratio of water, milk, coffee extract, and sucrose. Participants tasted 4 of 20 prototypes that were served in a monadic sequential order using a balanced incomplete block design. Data reported here are for participants randomly assigned to one of two research conditions: ideal scaling (n=129) or JAR scaling (n=132). For both conditions, participants rated overall liking using a 9-point hedonic scale. Four attributes (sweetness, milk flavor, coffee flavor and thickness) were evaluated. The reliability of an individual participant's ideal rating for an attribute was evaluated using the standard deviation of their ideal ratings (n=4). All data from a participant were eliminated from further analyses when his/her standard deviation of the ideal ratings for any of the four rated attributes was identified as a statistical outlier. This resulted in the elimination of 15 of 129 (12 %) of participants in the ideal scaling group. Multiple linear regression was employed to model liking as a function of "Too Little" or "Too Much" attribute intensities. Mean ideal ratings (averaged across participants) for all four attributes were significantly different from the central point of the scale (i.e., 50). However, Coffee flavor was the only attribute for which the mean ideal rating (57.2) fell outside the central 10% (45.0-55.0). Even so, the magnitude of "Too Little" and "Too Much" was not affected by the scaling method. The influence of the magnitude of "Too Little" and "Too Much" on liking was asymmetrical. Both scaling methods agreed that sweetness and coffee flavor were the main sensory attributes affecting liking. Overall, JAR scaling and ideal scaling were comparable for measuring "Too Little" and "Too Much", and identifying the main factors affecting liking.
Keywords: Consumer behavior; coffee; formulation; milk; product development; scaling bias.