The Effectiveness of Simple Decision Heuristics: A Case Study of Experts’ Forecasts of the Commercial Success of Early-Stage R&D Projects

ast that early-s evaluate 37 by examining cast. We use a eparately and of the experts' correct forecasts. We then compare predictions derived from the conjunctive model, analysts' ns. The 82.6%, out-of-time tests. Results indicate that simple decision heuristics perform better than ABSTRACT We investigate the decision heuristic used by experts to forec stage R&D projects are subsequently commercialized. Expert project characteristics and subjectively combine data on all cues both critical flaws as well as positive factors to arrive at a fore conjunctive model that sums " good " and " bad " cue counts s achieve a 94.1% classification accuracy forecasts and a statistical model with future project commercializatio conjunctive model correctly predicts 86.0%, experts correctly predict while a statistical model correctly predicts 78.6% in out-of-sample, statistically derived decision rules in a real setting.