Equate-to-differentiate approach: an application in binary choice under uncertainty

A descriptive model of decision making under uncertainty is developed in which each option of binary choice is represented by N possible-outcome dimensions. The choice behavior is thus modeled as a process in which the individual equates smaller difference between options on one (or some) possible-outcome dimension(s), but differentiates greater possible-outcome dimensional difference as the determinant of the final choice. Eight experimental problems involving known and unknown possible outcomes were designed to test the model.