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“Take-the-Best” and Other Simple Strategies: Why and When they Work “Well” with Binary Cues

“Take-the-Best” and Other Simple Strategies: Why and When they Work “Well” with Binary Cues The effectiveness of decision rules depends on characteristics of both rules and environments. A theoretical analysis of environments specifies the relative predictive accuracies of the “take-the-best” heuristic (TTB) and other simple strategies for choices between two outcomes based on binary cues. We identify three factors: how cues are weighted; characteristics of choice sets; and error. In the absence of error and for cases involving from three to five binary cues, TTB is effective across many environments. However, hybrids of equal weights (EW) and TTB models are more effective as environments become more compensatory. As error in the environment increases, the predictive ability of all models is systematically degraded. Indeed, using the datasets of Gigerenzer et al. (1999, Simple Heuristics That Make Us Smart, New York: Oxford University Press), TTB and similar models do not predict much better than a naïve model that exploits dominance. Finally, we emphasize that the results reported here are conditional on binary cues. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Theory and Decision Springer Journals

“Take-the-Best” and Other Simple Strategies: Why and When they Work “Well” with Binary Cues

Hogarth, Robin; Karelaia, Natalia
Theory and Decision , Volume 61 (3) – Sep 6, 2006
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References (23)

Publisher
Springer Journals
Copyright
Copyright © 2006 by Springer
Subject
Economics; Economic Theory/Quantitative Economics/Mathematical Methods; Game Theory, Economics, Social and Behav. Sciences; Operation Research/Decision Theory; Behavioral/Experimental Economics; Statistics for Business/Economics/Mathematical Finance/Insurance
ISSN
0040-5833
eISSN
1573-7187
DOI
10.1007/s11238-006-9000-8
Publisher site
See Article on Publisher Site

Abstract

The effectiveness of decision rules depends on characteristics of both rules and environments. A theoretical analysis of environments specifies the relative predictive accuracies of the “take-the-best” heuristic (TTB) and other simple strategies for choices between two outcomes based on binary cues. We identify three factors: how cues are weighted; characteristics of choice sets; and error. In the absence of error and for cases involving from three to five binary cues, TTB is effective across many environments. However, hybrids of equal weights (EW) and TTB models are more effective as environments become more compensatory. As error in the environment increases, the predictive ability of all models is systematically degraded. Indeed, using the datasets of Gigerenzer et al. (1999, Simple Heuristics That Make Us Smart, New York: Oxford University Press), TTB and similar models do not predict much better than a naïve model that exploits dominance. Finally, we emphasize that the results reported here are conditional on binary cues.

Journal

Theory and Decision – Springer Journals

Published: Sep 6, 2006

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