DECISION-MAKING UNDER UNCERTAINTY - A COMPARISON OF SIMPLE SCALABILITY, FIXED-SAMPLE, AND SEQUENTIAL-SAMPLING MODELS
DECISION-MAKING UNDER UNCERTAINTY - A COMPARISON OF SIMPLE SCALABILITY, FIXED-SAMPLE, AND SEQUENTIAL-SAMPLING MODELS
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DOI:
10.1037/0278-7393.11.3.538
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发表时间:
1985-01-01
影响因子:
2.6
通讯作者:
BUSEMEYER, JR
中科院分区:
文献类型:
--
作者:
BUSEMEYER, JR
Two studies with 12 undergraduate and graduate students investigated the cognitive processes involved in decision making under partial uncertainty. In both studies, Ss were given a choice between a certain alternative that produced a single known payoff and an uncertain alternative that produced a normal distribution of payoffs. Initially this distribution was unknown, and in Exp I it was learned through feedback from past decisions, whereas in Exp II it was learned by observing sample outcomes. In the 1st experiment, a response deadline was used to limit the amount of time available for making a decision. In the 2nd experiment, an observation cost was used to limit the number of samples that could be purchased. The mean and variance of the uncertain alternative and the value of the certain alternative were factorially manipulated to study their joint effects on choice probability, choice response time (Exp I), and number of observations purchased (Exp II). Results suggest that more attention should be given to theories of decision making that emphasize learning and memory retrieval (eg, the fixed-and the sequential-sampling models) rather than focusing exclusively on deterministic-algebraic theories (eg, subjective expected utility models).(30 ref)(PsycINFO Database Record (c) 2016 APA, all rights reserved)