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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

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.

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Chapter
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Publisher: Cambridge University Press
Print publication year: 2023

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References

Barron, G., & Erev, I. (2003). Small feedback-based decisions and their limited correspondence to description-based decisions. Journal of Behavioral Decision Making, 16(3), 215233. doi: 10.1002/bdm.443Google Scholar
Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1–3), 715. doi: 10.1016/0010-0277(94)90018-3Google Scholar
Benartzi, S., & Thaler, R. H. (1995). Myopic loss aversion and the equity premium puzzle. Quarterly Journal of Economics, 110(1), 7392. doi: 10.2307/2118511CrossRefGoogle Scholar
Denrell, J. (2005). Why most people disapprove of me: Experience sampling in impression formation. Psychological Review, 112(4), 951978.CrossRefGoogle ScholarPubMed
Denrell, J. (2007). Adaptive learning and risk taking. Psychological Review, 114(1), 398422. doi: 10.1037/0033-295X.114.1.177Google Scholar
Denrell, J. (2020). Adaptive sampling policies imply biased beliefs: A generalization of the hot stove effect. In S. Denison., M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings of the 42nd annual conference of the cognitive science society (pp. 1809–1815).Google Scholar
Denrell, J., & March, J. G. (2001). Adaptation as information restriction: The hot stove effect. Organization Science, 12(5), 523538.CrossRefGoogle Scholar
Denrell, J., Sanborn, A., & Spicer, J. (2021). Learning from feedback: Exemplar versus rule-based algorithms. Working Paper.Google Scholar
Dittmar, A., & Duchin, R. (2016). Looking in the rearview mirror: The effect of managers’ professional experience on corporate financial policy. Review of Financial Studies, 29(3), 565602. doi: 10.1093/rfs/hhv051Google Scholar
Elwin, E., Juslin, P., Olsson, H., & Enkvist, T. (2007). Constructivist coding: Learning from selective feedback. Psychological Science, 18(2), 105110. doi: 10.1111/j.1467-9280.2007.01856.xGoogle Scholar
Fazio, R. H., Eiser, J. R., & Shook, N. J. (2004). Attitude formation through exploration: Valence asymmetries. Journal of Personality and Social Psychology, 87(3), 293311.CrossRefGoogle ScholarPubMed
Fetchenhauer, D., & Dunning, D. (2010). Why so cynical? Asymmetric feedback underlies misguided skepticism regarding the trustworthiness of others. Psychological Science, 21(2), 189193. doi: 10.1177/0956797609358586Google Scholar
Gilovich, T. (1991). How we know what isn’t so: The fallibility of human reason in everyday life. New York: Simon & Schuster.Google Scholar
Hertwig, R., Barron, G., Weber, E. U., & Erev, I. (2004). Decisions from experience and the effect of rare events in risky choice. Psychological Science, 15(8), 534539. doi: 10.1111/j.0956-7976.2004.00715.xGoogle Scholar
Ilan, T., Katsnelson, E., Motro, U., Feldman, M. W., & Lotem, A. (2013). The role of beginner’s luck in learning to prefer risky patches by socially foraging house sparrows. Behavioral Ecology, 24(6), 13981406. doi: 10.1093/beheco/art079Google Scholar
Kim, Y. (2020). Customer retention under imperfect information. Working Paper. doi: 10.2139/ssrn.3709043.CrossRefGoogle Scholar
Larcom, S., Rauch, F., & Willems, T. (2017). The benefits of forced experimentation: Striking evidence from the London underground network. Quarterly Journal of Economics, 132(4), 20192055. doi: 10.1093/qje/qjx020Google Scholar
Larrick, R. P., & Wu, G. (2007). Claiming a large slice of a small pie: Asymmetric disconfirmation in negotiation. Journal of Personality and Social Psychology, 93(2), 212233. doi: 10.1037/0022-3514.93.2.212CrossRefGoogle ScholarPubMed
Le Mens, G., & Denrell, J. (2011). Rational learning and information sampling: On the “naivety” assumption in sampling explanations of judgment biases. Psychological Review, 118(2), 379392. doi: 10.1037/a0023010Google Scholar
Le Mens, G., Kovács, B., Avrahami, J., & Kareev, Y. (2018). How endogenous crowd formation undermines the wisdom of the crowd in online ratings. Psychological Science, 29(9), 14751490. doi: 10.1177/0956797618775080CrossRefGoogle ScholarPubMed
March, J. G. (1996). Learning to be risk averse. Psychological Review, 103(2), 309319.CrossRefGoogle Scholar
Plonsky, O., & Erev, I. (2017). Learning in settings with partial feedback and the wavy recency effect of rare events. Cognitive Psychology, 93, 1843. doi: 10.1016/j.cogpsych.2017.01.002Google Scholar
Plonsky, O., Teodorescu, K., & Erev, I. (2015). Reliance on small samples, the wavy recency effect, and similarity-based learning. Psychological Review, 122(4), 621647. doi: 10.1037/a0039413Google Scholar
Shepard, R. N. (1987). Toward a universal law of generalization for psychological science. Science, 237(4820), 13171323.CrossRefGoogle Scholar
Shteingart, H., Neiman, T., & Loewenstein, Y. (2013). The role of first impression in operant learning. Journal of Experimental Psychology: General, 142(2), 476488. doi: 10.1037/a0029550CrossRefGoogle ScholarPubMed
Teodorescu, K., & Erev, I. (2014). On the decision to explore new alternatives: The coexistence of under- and over-exploration. Journal of Behavioral Decision Making, 27(2), 109123. Retrieved from https://onlinelibrary.wiley.com/doi/10.1002/bdm.1785 doi: 10.1002/bdm.1785Google Scholar
Thaler, R. H., Tversky, A., Kahneman, D., & Schwartz, A. (1997). The effect of myopia and loss aversion on risk taking: An experimental test. Quarterly Journal of Economics, 112(2), 647661. doi: 10.1162/003355397555226Google Scholar
Twain, M. (1897). Following the equator: A journey around the world. Hartford, CT: American Publishing Co.Google Scholar
Weiss-Cohen, L., Konstantinidis, E., & Harvey, N. (2021). Timing of descriptions shapes experience-based risky choice. Journal of Behavioral Decision Making, 34(1), 6684. doi: 10.1002/bdm.2197CrossRefGoogle Scholar
Woiczyk, T. K. A., Lauenstein, F., & Le Mens, G. (2021). The hot kitchen effect: Categories, generalization, and exploration. Working Paper.Google Scholar
Wright, R. J., Rakow, T., & Russo, R. (2017). Go for broke: The role of somatic states when asked to lose in the Iowa Gambling Task. Biological Psychology, 123, 286293. doi: 10.1016/j.biopsycho.2016.10.014CrossRefGoogle ScholarPubMed
Yechiam, E., & Busemeyer, J. R. (2006). The effect of foregone payoffs on underweighting small probability events. Journal of Behavioral Decision Making , 19(1), 116. doi: 10.1002/bdm.509CrossRefGoogle Scholar
Yechiam, E., & Yakobi, O. (2018). Loss attention and the Equity Premium Puzzle: An examination of the myopic loss aversion hypothesis. Working Paper.Google Scholar
Zion, U. B., Erev, I., Haruvy, E., & Shavit, T. (2010). Adaptive behavior leads to under-diversification. Journal of Economic Psychology, 31(6), 985995. doi: 10.1016/j.joep.2010.08.007CrossRefGoogle Scholar

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