In the experiments, we vary the representativeness of the laboratory sample to the market of interest. We find that while behavioral forecasts are significantly impacted by sample/market similarity, neural forecasts are not.
In this paper we show that the decision-making process can be broken down into components, some of which are more widely shared across individuals then others. Neural measures of the shared components consequently lead to more accurate aggregate level forecasts.
Can AI's predictive power reshape the #music landscape? Take a break at @ADE_NL to join this amazing session where RSM’s Dr Alex @genevsky will be talking #AI, #neuroforecasting and predicting hit music! https://t.co/cjlKWglnrn
Our collaborative group has projects exploring a large range of topics including social decision-making, emotions, dishonesty, charitable giving, consumer decisions, social credit systems, and forecasting
@GregoryRSL Would be interesting to allow students to self select into the more vs less structured versions of the course and measure their experience and performance