谷歌浏览器插件
订阅小程序
在清言上使用

Do Smarter People Employ Better Decision Strategies? the Influence of Intelligence on Adaptive Use of the Recognition Heuristic

Journal of behavioral decision making(2017)

引用 11|浏览7
暂无评分
摘要
Within the adaptive toolbox approach, it has repeatedly been shown that, on average, people tend to adapt their decision strategies to the decision context. Building upon these results, we investigated whether individuals systematically differ in their ability to successfully adapt to the situation when applying the fast-and-frugal recognition heuristic (RH). In decisions between recognized and unrecognized choice objects, individuals can base their choices solely on recognition, as predicted by the RH, or they can use further knowledge retrieved from memory. Since intelligence has been conceived as the ability to successfully adapt to different situations, we expected intelligence to influence the degree of adaptive use of the RH. To test this hypothesis, we first re-analyzed data that referred to a decision domain for which RH-use is known to perform well. As expected, individual RH-use increased with general intelligence. Next, we designed an experiment addressing individual RH-use in two new decision domains, one domain for which RH-use was less effective than knowledge-use and another domain for which both strategies were about equally effective. In addition, we tested whether fluid or crystallized intelligence best predicts adaptive use of the RH. RH-use was found to decrease with fluid but not crystallized intelligence when RH-use was less effective than use of further knowledge. In contrast, there was no significant association between either type of intelligence and RH-use when none of the two strategies was optimal. We conclude that adaptive use versus non-use of the RH is moderated by fluid intelligence. Copyright (c) 2017 John Wiley & Sons, Ltd.
更多
查看译文
关键词
adaptive decision making,recognition heuristic,intelligence,multinomial processing tree models,hierarchical Bayesian modeling
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要