â€œTake-the-Bestâ€\x9D and Other Simple Strategies: Why and When they Work â€œWellâ€\x9D with Binary Cues
AbstractThe 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
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Bibliographic InfoArticle provided by Springer in its journal Theory and Decision.
Volume (Year): 61 (2006)
Issue (Month): 3 (November)
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Web page: http://www.springerlink.com/link.asp?id=100341
decision making; bounded rationality; lexicographic rules; take-the-best; equal weighting;
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