We study a problem where a DM is simultaneously presented with a set of risky binary options that concurrently increase in their value, but decrease in their probability of being realized. Further, the DM operates under the restriction of being able to accept only the most valuable option that is realized. In a single stage the DM is called upon to select a set of risky options where each selection is costly. Such decision scenarios have natural analogues in the complex world. Take for example the process of a student applying for admission to graduate school. Here the options are differently valued (some schools are more preferred than others), differently likely (some schools are harder to get in to than others). Additionally these features are negatively correlated and the student can only go to, at most, one school. We refer to this decision context as an Admissions Problem. We present data from a laboratory experiment where financially motivated DMs were presented with a variety of Admission Problems with varying probability structures and contrast these results to the normative solution. Results indicate that DMs are generally under-applying (not selecting enough risky options from a set). This bias is persistent even with experience and feedback. Generally DMs did not select risky options with middle-high ranks when they should have. Conversely DMs did select lower ranked options when they should not have. These results are consistent with well known decision biases including risk and loss aversion. |