Neural Network Modeling of Gist and Verbatim in Business Decision Making

被引:0
|
作者
Levine, Daniel S. [1 ]
Chen, Kay-Yut [2 ]
机构
[1] Univ Texas Arlington, Dept Psychol, Arlington, TX 76019 USA
[2] Univ Texas Arlington, Dept Informat Syst & Operat Management, Arlington, TX 76019 USA
关键词
AFFECTIVE PSYCHOLOGY;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A neural network based on fuzzy trace theory and previously used to model decisions by a retailer on how much of a product to purchase (the "newsvendor problem") is extended to a case with a particularly salient gist. This is the case where the newsvendor is a manager who receives a bonus if profit is at least at a target value. The gist is that in order to maximize the probability of a bonus the newsvendor should buy exactly the minimum amount that makes the target profit possible, that is, target divided by (price per item minus cost per item). The network includes amygdala and orbitofrontal cortex for emotional evaluation, anterior cingulate for behavioral planning, and striatum, thalamus, and motor cortex for behavioral execution.
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页数:8
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