Inhaltszusammenfassung

Goldstein and Gigerenzer (2002) described the recognition heuristic as a fast, frugal, and effective decision strategy. However, most studies concerning the recognition heuristic have been conducted in static domains, that is, in domains where it could plausibly be argued that relevant variables stay relatively constant. Yet the question is whether the heuristic would also work in dynamic environments where the quality of the actors rises and falls, such as in sports. We tested performance of...Goldstein and Gigerenzer (2002) described the recognition heuristic as a fast, frugal, and effective decision strategy. However, most studies concerning the recognition heuristic have been conducted in static domains, that is, in domains where it could plausibly be argued that relevant variables stay relatively constant. Yet the question is whether the heuristic would also work in dynamic environments where the quality of the actors rises and falls, such as in sports. We tested performance of the recognition heuristic in a dynamic environment and used it to predict the outcomes of tennis matches in Wimbledon 2003. Recognition data of amateur tennis players and laypeople was used to build recognition rankings. These rankings correlated with official rankings and led to at least as good predictions. Simulations of individual choices showed high recognition validities of both amateurs (0.73) and laypeople (0.67). In a second study the recognition heuristic correctly predicted 90% of actual individual choices. Overall, the recognition heuristic may be effectively generalized to dynamic environments.» weiterlesen» einklappen

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DDC Sachgruppe:
Psychologie