EXTENDED ABSTRACT
Lists of ranked items (e.g., Business Week’s top 25 MBA pro-
grams, Car and Driver’s top 10 cars) are ubiquitous in Western cul-
ture. From a consumption standpoint, there is considerable evidence
that individuals nd these lists informative and in uential. There-
fore, it is important to know exactly how the information provided in
ranked lists is interpreted by users. Because a ranking is an ordinal
scale of measurement, there is no technical reason why an informa-
tion user should interpret items at adjoining ranks as having equal
differences in the ranked attribute. Yet, in the absence of speci c in-
formation about the ranked items, this equidistance seems reasonable
for the information user to assume. In fact, even academic researchers
have utilized linear functions that imply equidistance when modeling
the effects of changes in an organization’s rank on the outcomes and
policies of the ranked organizations (Monks and Ehrenberg 1999a, b)
In this research, we propose the existence of a cognitive bias
that overrides the presumption of equidistance between adjacent
ranks in the interpretation of ranked lists. This bias, which has im-
portant implications for consumer evaluations of items presented in
a ranked list, emerges due to our tendency to see complex and uncat-
egorized arrays, such as long lists of numbers, in terms of a smaller
set of categories. A consequence of this tendency to categorize is an
exaggeration of the perceived differences between items at adjoining
ranks that cross category boundaries.
Lists of ranked items (e.g., Business Week’s top 25 MBA pro-
grams, Car and Driver’s top 10 cars) are ubiquitous in Western cul-
ture. From a consumption standpoint, there is considerable evidence
that individuals nd these lists informative and in uential. There-
fore, it is important to know exactly how the information provided in
ranked lists is interpreted by users. Because a ranking is an ordinal
scale of measurement, there is no technical reason why an informa-
tion user should interpret items at adjoining ranks as having equal
differences in the ranked attribute. Yet, in the absence of speci c in-
formation about the ranked items, this equidistance seems reasonable
for the information user to assume. In fact, even academic researchers
have utilized linear functions that imply equidistance when modeling
the effects of changes in an organization’s rank on the outcomes and
policies of the ranked organizations (Monks and Ehrenberg 1999a, b)
In this research, we propose the existence of a cognitive bias
that overrides the presumption of equidistance between adjacent
ranks in the interpretation of ranked lists. This bias, which has im-
portant implications for consumer evaluations of items presented in
a ranked list, emerges due to our tendency to see complex and uncat-
egorized arrays, such as long lists of numbers, in terms of a smaller
set of categories. A consequence of this tendency to categorize is an
exaggeration of the perceived differences between items at adjoining
ranks that cross category boundaries.