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Publication details

Publisher: Springer

Place: Berlin

Year: 2019

Pages: 217-241

Series: Springer Series in Cognitive and Neural Systems

ISBN (Hardback): 9783030031039

Full citation:

Kay-Yut Chen, Daniel S. Levine, "Heuristics of numerical choice in economic contexts", in: Blended cognition, Berlin, Springer, 2019

Abstract

Many problems in the psychology of judgment and decision making that employ heuristics involve preferences between two or more alternatives. Other problems involve estimation of numerical quantities. In this chapter we discuss the heuristics of problems that combine both of these processes, in that they involve decisions among different amounts of a particular item. We review several examples of these kinds of heuristics applied to economic contexts, such as decisions about how much of an item to buy from a supplier or to sell to consumers. Then we discuss models and theories that can explain the use of these heuristics in decision making. These theories are partly based on behavioral data in memory and decision making, and partly based on neural networks that incorporate the functions of specific brain regions.

Publication details

Publisher: Springer

Place: Berlin

Year: 2019

Pages: 217-241

Series: Springer Series in Cognitive and Neural Systems

ISBN (Hardback): 9783030031039

Full citation:

Kay-Yut Chen, Daniel S. Levine, "Heuristics of numerical choice in economic contexts", in: Blended cognition, Berlin, Springer, 2019