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

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.)