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Making Each Unit Count

The Role of Discretizing Units in Quantity Expressions

Bibliographic Data

ID2237575
AuthorsChristophe Lembregts (0000-0002-5415-9063, Department of Marketing Management at Rotterdam School of Management, Erasmus University, DR Rotterdam, corresponding author), Bram Van Den Bergh (0000-0003-2145-6077, Department of Marketing Management at Rotterdam School of Management, Erasmus University, DR Rotterdam)
EditorsGita Johar, Rajesh Bagchi
Year2019
Volume45
Issue5
Pages1051-1067
Publication date2019-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Consumer Research (JOURNAL)
Journal identifiersISSN: 0093-5301 • E-ISSN: 1537-5277
PublisherOxford University Press (PUBLISHER • GB)
DOI10.1093/jcr/ucy036
OpenAlexW2796985867
LanguageEN
Citations received7
References cited62

Consumers typically infer greater quantity from larger numbers. For instance, a 500 gram box of chocolates appears heavier than a .5 kilogram box. By expressing quantities in alternative units or attribute dimensions, one can represent an otherwise identical quantity in a more versus less discretized manner (e.g., a box containing 25 chocolates vs. a box weighing 500 grams). Seven experimental studies show that a difference between more discretized quantities (e.g., 25 vs. 50 chocolates) appears larger relative to a difference between less discretized quantities (e.g., 500 grams vs. 1,000 grams), above and beyond effects of number magnitude. More discretized quantity expressions enhance the consumers’ ability to discriminate between choice options and can also nudge consumers to more favorable choices. Because more discretized quantities are more evaluable, expressing a quantity in terms of a collection of elements particularly helps individuals who are less numerically proficient. By identifying how discretization functions as a novel antecedent of evaluability and by distinguishing two different conceptualizations of numerosity (i.e., symbolic and perceptual numerosity), this article draws important connections between the numerical cognition literature and General Evaluability Theory.

Cognition · Cognitive psychology · Discretization · Mathematical analysis · Mathematical economics · Numerical cognition · Numerosity adaptation effect · Perception · Significant difference · Statistics · Applied Mathematics · Cognitive and developmental aspects of mathematical skills · Computer Science · Learning Styles and Cognitive Differences · Mathematics · Mathematics Education and Teaching Techniques · Psychology · Social Psychology

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Unique citing works7
Citations per year1
Citation span2019 - 2026 (8)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 7

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