Improving Quantitative Decision Making
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People’s lives are pervaded with quantitative information. For example, practically all products and services carry quantitative information ranging from nutritional content (e.g., “60 grams sugar content") to ecological impact (e.g., “6 liters/100 kilometers fuel consumption”). This widespread provision of quantitative information is generally encouraged because it should allow for better-informed decisions. In contrast with this assumption, a growing research stream has been documenting a large number of errors in decisions involving quantitative information. As such, the well-intentioned provision of quantitative information may be ineffective in improving individuals’ decisions. By using a combination of online, lab and field studies, this project will investigate how the metric (e.g., grams vs. cubes of sugar) in which information is described improves understanding of quantitative information. A first subproject will test whether metrics that lead individuals to think of quantitative information as a collection of discrete elements (a set of cubes, piles, bags…) engender a more natural understanding of quantitative information than nondiscrete metrics (liters, grams, pounds). A second subproject will investigate how using a discrete metric renders quantitative information to be more important in decisions: Do individuals rely more on quantitative information about sugar content when it is described in cubes than in grams? In a third subproject, I will focus on how discrete metrics may be particularly effective in two contexts in which most decision errors occur: due to a temporal (cognitive busyness) or chronic lack of ability (numeracy: the ability to process numerical concepts). For theory, the project will be among the first to turn attention to how individuals’ understanding of quantitative information and decision making can be improved. For practice, this project will provide policy makers with an easy-to-implement, yet relevant intervention that is applicable to all domains involving quantitative decision making.
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