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Chapter 4 - The Hot Stove Effect

from Part I - Historical Review of Sampling Perspectives and Major Paradigms

Published online by Cambridge University Press:  01 June 2023

By
Jerker Denrell  and
Gaël Le Mens
Edited by
Klaus Fiedler ,
Peter Juslin  and
Jerker Denrell
Klaus Fiedler
Affiliation:
Universität Heidelberg
Peter Juslin
Affiliation:
Uppsala Universitet, Sweden
Jerker Denrell
Affiliation:
University of Warwick
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Summary

People revisit the restaurants they like and avoid the restaurants with which they had a poor experience. This tendency to approach alternatives believed to be good is usually adaptive but can lead to a systematic bias. Errors of underestimation (an alternative is believed to be worse than it is) will be less likely to be corrected than errors of overestimation (an alternative is believed to be better than it is). Denrell & March (2001) called this asymmetry in error correction the “Hot Stove Effect.” This chapter explains the basic logic behind the Hot Stove Effect and how this bias can explain a range of judgment biases. We review empirical studies that illustrate how risk aversion and mistrust can be explained by the Hot Stove Effect. We also explain why even a rational algorithm can be subject to the same bias.

Keywords

samplingnegativity biasHot Stove EffectlearningBayesian modelsrationalityexploration
Type
Chapter
Information
Sampling in Judgment and Decision Making , pp. 90 - 112
Publisher: Cambridge University Press
Print publication year: 2023

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