title: Maximizing overall liking results in a superior product to minimizing deviations from ideal ratings: an optimization case study with coffee-flavored milk.
abstract: In just-about-right (JAR) scaling and ideal scaling, attribute delta (i.e., "Too Little" or "Too Much") reflects a subject's dissatisfaction level for an attribute relative to their hypothetical ideal. Dissatisfaction (attribute delta) is a different construct from consumer acceptability, operationalized as liking. Therefore, we hypothesized minimizing dissatisfaction and maximizing liking would yield different optimal formulations. The objective of this research was to compare product optimization strategies, i.e. maximizing liking vis-à-vis minimizing dissatisfaction. Coffee-flavored dairy beverages (n = 20) were formulated using a fractional mixture design that constrained the proportions of coffee extract, milk, sucrose, and water. Participants (n = 388) were randomly assigned to one of three research conditions, where they evaluated 4 of the 20 samples using an incomplete block design. Samples were rated for overalllikingand for intensity of the attributessweetness, milk flavor, thicknessandcoffee flavor. Where appropriate, measures of overall product quality (Ideal_DeltaandJAR_Delta) were calculated as the sum of the absolute values of the four attribute deltas. Optimal formulations were estimated by: a) maximizingliking; b) minimizingIdeal_Delta; or c) minimizingJAR_Delta. A validation study was conducted to evaluate product optimization models. Participants indicated a preference for a coffee-flavored dairy beverage with more coffee extract and less milk and sucrose in the dissatisfaction model compared to the formula obtained by maximizingliking. That is, whenlikingwas optimized, participants generally liked a weaker, milkier and sweeter coffee-flavored dairy beverage. Predictedlikingscores were validated in a subsequent experiment, and the optimal product formulated to maximizelikingwas significantly preferred to that formulated to minimize dissatisfaction by a paired preference test. These findings are consistent with the view that JAR and ideal scaling methods both suffer from attitudinal biases that are not present when liking is assessed. That is, consumers sincerely believe they want 'dark, rich, hearty' coffee when they do not. This paper also demonstrates the utility and efficiency of a lean experimental approach.
authors.affiliation: Sensory Evaluation Center, College of Agricultural Sciences, The Pennsylvania State University, University Park, PA, USA ; Department of Food Science, College of Agricultural Sciences, The Pennsylvania State University, University Park, PA, USA.
authors.forename: Bangde
authors.initials: B
authors.lastname: Li
authors.affiliation: Sensory Evaluation Center, College of Agricultural Sciences, The Pennsylvania State University, University Park, PA, USA ; Department of Food Science, College of Agricultural Sciences, The Pennsylvania State University, University Park, PA, USA.
authors.forename: John E
authors.initials: JE
authors.lastname: Hayes
authors.affiliation: Department of Food Science, College of Agricultural Sciences, The Pennsylvania State University, University Park, PA, USA.
authors.forename: Gregory R
authors.initials: GR
authors.lastname: Ziegler
keywords: Consumer behavior; JAR scaling; coffee; dissatisfaction; ideal scaling; product optimization