The Impact of Overconfidence on the Evaluation of Innovations : An Information Market Experiment

The evaluation of new products and innovative technologies is a core task of innovation management. Without valid innovation evaluation, companies fail to identify promising endeavors for future business success. However, the evaluation of innovations is characterized by environments where uncertainty is high and strategic context is poorly understood. A relatively new strand of research promisingly taps heterogeneous individual expectations or the wisdom of crowds to generate valid predictions in such environments. But there is strong evidence that aggregating subjective expectations can yield biased results as individuals often draw highly biased conclusions from available information. Among important individual evaluators of innovations such as entrepreneurs, inventors and business decision makers, overconfidence is the most prominent and important bias. Overconfidence leads individuals to systematically overestimate their evaluation capabilities. We report an experiment that explores the impact of overconfidence on individual behavior in innovation evaluation tasks. We focus a promising method to tap crowd wisdom known as information- or prediction markets, which aggregate individual evaluations of new product success or innovative idea potential via market mechanisms. We induce overconfidence experimentally and study how overconfident individuals interact on these platforms. Our results show that overconfident individuals turn evaluations into actions earlier. They pursue their predictions with more vigor, are more likely to act according to initial evaluations by disregarding contradictory information and are less willing to change a priori predictions after innovation evaluation tasks finish