Information markets are interactive platforms on which virtual stocks represent different innovation ideas or concepts. The market participants trade shares of these stocks, such that the resulting stock prices indicate the success potential of the different innovations. Information markets are a promising tool for predicting the success of innovations as they help to pool heterogeneous beliefs that evaluators hold regarding the prediction task.
The main goal of this project is to foster understanding about the impact of the overconfidence bias on the evaluation of innovations via information markets. The research uses experimental studies to explore how overconfidence impacts individual behavior of market participants and, in turn, how overconfidence affects the prognostic validity of the market result.
The findings of this research contribute to the understanding of how participants of information markets behave. Particularly, the results can help to design information markets that mitigate the influence of judgmental biases on the quality of the prediction.