Decision field theory provides for a mathematical foundation leading to a dynamic, stochastic theory of decision behavior in an uncertain environment. This theory is used to explain (a) violations of stochastic dominance, (b) violations of strong stochastic transitivity, (c) violations of independence between alternatives, (d) serial position effects on preference, (e) speed-accuracy trade-off effects in decision making, (f) the inverse relation between choice probability and decision time, (g) changes in the direction of preference under time pressure, (h) slower decision times for avoidance as compared with approach conflicts, and (i) preference reversals between choice and selling price measures of preference. The proposed theory is compared with 4 other theories of decision making under uncertainty.

A mathematical theory and related experimental methodology are developed that permit strong, converging tests of parallel versus serial versus channel summation processing and of exhaustive versus self-terminating processing. An experimental design is used for two studies, in which the presence or absence of a target in each of two positions, is factorially combined with two levels of brightness (a version of the double factorial paradigm). When both targets are present (redundant target condition) the two levels of brightness permit factorial technology to determine mental architecture and stopping rules. Comparison of the single versus double target conditions allows capacity analyses that strongly reinforce the double target factorial phase of the investigation. The results provide decisive support for parallel channels with either a self-terminating stopping rule or a coactive summation of information. General serial models and any variety of exhaustive processing were conclusively falsified.