Subtraction or Division: Evaluability Moderates Reliance on Absolute Differences versus Relative Differences in Numerical Comparisons

Abstract

Specifications of many product attributes (prices, review scores, fuel efficiency, calories, computer processor speed, etc.) are numerical. When comparing alternatives, consumers often need to judge how much larger or smaller one value is than another (say x and y). How do they make such a judgment? The literature suggests that people can rely on either the absolute difference (x – y) or relative difference (x / y). Importantly, relying on the absolute versus relative difference might lead to divergent outcomes. Therefore, this research aims to identify one factor that moderates consumers’ reliance on absolute versus relative differences. Specifically, we propose that when the attribute is easy to evaluate (i.e., when consumers have clear reference information), people tend to compute and rely on absolute differences to make comparative judgments. By contrast, when the attribute evaluability is low (i.e., reference information is lacking), they tend to compute the relative difference. Results from six studies provide convergent evidence for this proposition and demonstrate its downstream effects on preference and judgments.