Multiattribute decision making in context: A dynamic neural network methodology.

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    A theoretical structure for multiattribute decision making is presented, based on a dynamical system for incorporating affective and rational variables.  This enables modeling of problems that elude two prevailing economic decision theories: subjective expected utility theory and prospect theory.  The networks is unlike some that fit economic data by choosing optimal weights or coefficients within a predetermined mathematical framework.  Rather, the framework itself is based on principles used elsewhere to model many other behavioral functions.  Different, interconnected modules within the network encode (a) attributes of objects among which choices are made, (b) object categories, and (c) goals of the decision maker.  An example is utilized to simulate the actual consumer choice between old and new versions of Coca-Cola.  Potential applications are also discussed to market decisions involving negotiations between participants, such as international petroleum traders. (This was also the subject of a column in Science, September 3, 1993.)