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Past research has identified that innovation portfolio management is about efficiently managing the right innovation portfolio projects. However, the relevant literature has fairly unobserved decision processes which help to maximize the value of the entire innovation portfolio. This work analyzed decision procedures within the context of innovation portfolio management; especially, the project go/stop-decision processes. Founded on a theoretical basis two decision making experiments were developed and a distinct set of hypotheses by two large-scale experimental studies were tested.
The present work is aimed at making a valuable contribution to conceptual research about decision making in the context of innovation portfolio management, and the experimental based research field. The results of these studies help to get a detailed understanding of the decision making processes and may lead to a better understanding of project management within an innovation portfolio by firms and by decision makers in general.
We use data from the Consensus Economics Forecast Poll to analyze how current account forecasters form expectations. Our results suggest that forecasts do not satisfy traditional unbiasedness and orthogonality criteria for forecast rationality. In addition, we find anti-herding behavior among forecasters for the Euro area and G7 countries. We also show that the cross-sectional heterogeneity in anti-herding is associated with cross-sectional heterogeneity in forecast accuracy. More specifically, we find some evidence indicating that forecasters who tend to herd provide more accurate forecasts than their colleagues who follow an anti-herding strategy.