Rankings, in which various choice options are ranked on some attribute, are a particularly popular decision aid. The current proposal argues that the way options are presented in rankings might actually create an evaluation bias, which we call the linearity effect.
Attribute values are often asymmetrically distributed, with relatively more low attribute levels (e.g., lower prices or quality) than high attribute levels. For example, when ranking hotels on price, the difference between the first options will be smaller than the difference between options lower on the list, since there will be more hotels with relatively low prices than with relatively high prices. While previous research has demonstrated that people are aware of this asymmetry and take it into account when evaluating options, we hypothesize that the structure of rankings frame peoples’ evaluations as more linear. Hence, they will perceive the difference between all options as more equal (Objective 1).
Moreover, we will explore the possible cause for this linearity effect (Objective 2). We propose that the linearity effect is caused by the interaction of the ease-of-processing of the rank information and its relevancy to the task. When rankings are used to evaluate a set of choice options, consumers will use the rank information to understand the relationship between options.
However, by following the linear trend of the rank information, they will ignore the asymmetric distribution of the attribute values.