The effect of regulatory focus on the shape of probability-weighting function: Evidence from a cross-modality matching method

Prospect theory (Kahneman & Tversky, 1979, 1984) suggests that when people are presented with objective probabilities they (a) underweight high probabilities (e.g., behave as if 99% likelihood of an event is lower than 99%), (b) overweight low probabilities, and (c) are relatively insensitive to differences among moderate probabilities. We hypothesized that these biases will be found under prevention focus (Higgins, 1997), which can be triggered by security needs, and monetary considerations; but reversed under promotion focus (Higgins, 1997), which can be triggered by self-actualization needs. To test the hypothesis, we developed a crossmodality matching task that allows tapping probability transformations independently from the value of an event. In two studies, participants (N = 116 and N = 156) drew portions of circles that represented their transformations of 13 different stated probabilities regarding three scenarios (either promotion or prevention). Results in the prevention condition were consistent with prospect theory-providing validity for the cross-modality matching method. Results in the promotion condition indicated both a general elevation (overweighting), which was most evident for moderate and moderate-high probabilities, and minor underweighting for probabilities larger than .80. In the second study, we also assessed chronic-regulatory focus which yielded effects similar to the manipulated-regulatory focus. In both studies, some individuals in the promotion focus groups yielded probability weighting functions with a curvature opposite the predictions of prospect theory; and within each experimental condition there were additional significant differences in the transformation yielded by the putatively similar three scenarios. The results indicate that our crossmodality matching method is very sensitive to context effects and hint at the possibility of applying similar cross-modality matching methods to explore other decision-making processes such as value functions (Kahneman & Tversky, 1979). (C) 2004 Elsevier Inc. All rights reserved.