â€œTake-the-Bestâ€\x9D and Other Simple Strategies: Why and When they Work â€œWellâ€\x9D 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 â€œtake-the-bestâ€\x9D 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 etÂ al. (1999, Simple Heuristics That Make Us Smart, New York: Oxford University Press), TTB and similar models do not predict much better than a naÃ¯ve model that exploits dominance. Finally, we emphasize that the results reported here are conditional on binary cues. Copyright Springer 2006
Volume (Year): 61 (2006)
Issue (Month): 3 (November)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gigerenzer, Gerd & Todd, Peter M. & ABC Research Group,, 2000. "Simple Heuristics That Make Us Smart," OUP Catalogue, Oxford University Press, number 9780195143812.
- Robin Hogarth & Natalia Karelaia, 2004. "Ignoring information in binary choice with continuous variables: When is less 'more'?," Economics Working Papers 742, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2004.