It is well known that consumer price judgments affect brand choice and that these judgments are constructed by comparing the price of a brand to one or more prices in the judgment context, typically referred to as reference prices. Predicting price judgments is straightforward when the brand price is compared with a single reference price (i.e., price judgment = brand price – reference price), but how should price judgments be modeled when consumers compare the brand price with more than one reference price? Current marketing practice assumes that consumers compare the brand price with a central tendency representation of the reference price distribution (i.e., price judgment = brand price – mean reference price). However, recent experimental research has demonstrated that consumers can employ a vast array of reference prices in constructing price judgments and that these judgments are affected by additional characteristics of the reference price distribution, such as range, skew, and modality.
To account for effects beyond the first moment of a reference price distribution, the authors specify price judgments using range–frequency theory, which maps the location of the brand price onto two psychological judgment scales (range and frequency). The authors then develop operational procedures to use range–frequency theory in mixed multinomial logit models and test the approach using scanner panel data from three product categories. In all cases, range–frequency theory accounts for reference price effects beyond those captured by central tendency models. Moreover, the influence of range–frequency price judgments increases with the variance and skew of the reference price distribution. Finally, the relative weight of the range and frequency values is influenced by whether the consumer perceives a trend of brand prices or is a coupon user. Consumers who are exposed to a price trend are more attuned to frequency effects, whereas those who use coupons are more influenced by range effects.
These findings provide several implications for marketing theory and practice. Because choice behavior is affected by the reference price distribution, the authors recommend using range–frequency price judgments in models of brand choice, particularly when the reference price distributions are not well characterized by the first moment. The findings also suggest an alternative view to the notion that consumers integrate reference prices into a single prototypical abstraction, such as the distribution’s mean. Rather, the results are more consistent with exemplar theory, which suggests that prices are represented by the individual instances themselves and that the influence of any specific instance on price judgments may be moderated by several factors (e.g., price trend, coupon usage). This theoretical distinction is important for managers who want to understand and predict the distributional effects of their pricing strategies. For example, when choosing between alternative high–low pricing strategies with the same mean price, should brand managers use less frequent deep discounts or more frequent shallow discounts? Although central tendency models predict that both strategies will have the same impact on consumers, range–frequency theory predicts that managers should consider the latter approach.
Biography
Ronald W. Niedrich is Associate Professor of Marketing in the E.J. Ourso College of Business at Louisiana State University. His research focuses on consumer judgment and decision making and appears in various marketing journals, including Journal of Marketing Research, Journal of Consumer Research, Journal of the Academy of Marketing Science, Journal of Retailing, Journal of Advertising, and Journal of Business Research. Ron has a BS in Engineering from Clemson University, an MBA from the College of William and Mary, and a PhD in Business Administration from the University of South Carolina.
Danny Weathers is Associate Professor of Marketing in the E.J. Ourso College of Business at Louisiana State University. His research focuses on methodological and measurement issues, pricing, and online marketing and appears in various marketing and statistics journals, including Journal of Marketing Research, Journal of Retailing, International Journal of Research in Marketing, Journal of Business Research, and Journal of Applied Statistical Science. Danny has a BS in Math from Clemson University, an MS in Statistics from the University of South Carolina, and a PhD in Business Administration from the University of South Carolina.
R. Carter Hill is Ourso Family Professor of Econometrics in the E.J. Ourso College of Business at Louisiana State University. His research focuses on the theory and practice of microeconometrics and appears econometrics and statistics journals, including Journal of the American Statistical Association, Journal of Business and Economic Statistics, Journal of Econometrics, and Review of Economics and Statistics. Carter has Economics degrees from Duke (BA), Western Illinois (MA), and University of Missouri–Columbia (Ph.D.)
David R. Bell is Associate Professor of Marketing in the Wharton School at the University of Pennsylvania. His research focuses on individual and interdependent choice behavior, with applications in retail settings, and appears in various marketing journals, including Journal of Marketing Research, Journal of Consumer Research, Management Science, Marketing Science, Quantitative Marketing and Economics, Journal of Retailing, and Marketing Letters. David has an MCom in Marketing and International Business from University of Auckland, an MS in Statistics from Stanford University, and a PhD in Business from Stanford University.
Journal Marketing Research, Volume 46, Number 5, October 2009
View Table of Contents.