An important problem in descriptive and prescriptive research in decision making is to identify “regions of rationality,” i.e., the areas for which heuristics are and are not effective. To map the contours of such regions, we derive probabilities that heuristics identify the best of m...

An important problem in descriptive and prescriptive research in decision making is to identify "regions of rationality," i.e., the areas for which simple, heuristic models are and are not effective. To map the contours of such regions, we derive probabilities that models identify the best of m...

An important problem faced by boundedly rational agents is to identify 'regions of rationality,' i.e., the areas for which simple, boundedly rational models are and are not effective. To map the contours of such regions, we derive probabilities that models identify the best of m alternatives (m ...

When can a single variable be more accurate in binary choice than multiple sources of information? We derive, analytically, the probability that a single variable (SV) will correctly predict one of two choices when both criterion and predictor are continuous variables. We further provide...

People experience difficulty in facing tradeoffs in multi-attribute choice. However, to what extent do they need to face these tradeoffs explicitly? We examine choices by simple tradeoff - avoiding models in environments where "true" preferences are linear and attributes are characterized by...