TY - JOUR
AU - Godfrey, Ellen G.
AB - This manuscript uses areformulation of Vroom's(1964) VIE theory to illustrate the potential value ofneuropsychologically based models of cognitive processes. Vroom's theory posits thatpeople's decisions are determined by their affective reactions to certain outcomes(valences), beliefs about the relationship between actions and outcomes (expectancies),and perceptions of the association between primary and secondary outcomes(instrumentalities). One of the major criticisms of this type of theory is that thecomputations it requires are unrealistically time-consuming and often exceed workingmemory capacity. In this paper, we maintain that if an individual has extensive experiencewith a problem situation, he or she can process decisions about that situation usingneural networks that operate implicitly so that cognitive resources are not exhausted bysimple computations; instead, the computations are performed implicitly by neuralnetworks. By thinking about VIE from a neural network standpoint, at least one of itsproblems is eliminated, and several new insights into decision-making are provided. We usesimulation methodology to show that such a model is both viable and can reflect theeffects of current goals on choice processes.
TI - Integrating Neural Networks into Decision-Making and Motivational Theory: Rethinking VIE Theory
JF - Canadian Psychology/Psychologie Canadienne
DO - 10.1037/h0085815
DA - 2003-02-01
UR - https://www.deepdyve.com/lp/american-psychological-association/integrating-neural-networks-into-decision-making-and-motivational-aPdC3ECoto
SP - 21
EP - 38
VL - 44
IS - 1
DP - DeepDyve
ER -