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Moderators for Partition Dependence in Prediction Markets

  • Simon KlokerEmail author
  • Tim Straub
  • Christof Weinhardt
Article
  • 34 Downloads

Abstract

Every investment decision by organizations is an implicit expression of a prediction on the future state of companies, demand trends, future challenges, or politics. Usually, decision makers can chose between different options to invest and also tend to diversify investments in order to reduce risk. Research on cognitive processing, however, showed that unconscious heuristics triggered by “heuristic cues” influence such decisions in an irrational manner. Partition dependence, the partition of the state space, is such a heuristic cue that leads to an irrational bias in the assessment of probabilities towards a uniform distribution. This work demonstrates that this bias is also persistent in group-based forecasting. We explain and predict the occurrence of the partition dependence bias by applying the Dual-Process Theory of cognitive processing. The results of our three consecutive experiments suggest that besides task complexity, individual expertise, and motivation are moderators for the occurrence of partition dependence. We contribute to the research of biases in forecasting by applying approaches of the Dual-process Theories to explain the occurrence of partition dependence for the first time and shed light on future pathways in this research field.

Keywords

Partition dependence Prediction markets Group-based forecasting Heuristics Cognitive biases Heuristic Systematic Model 

Notes

Acknowledgements

We thank the Deutsche Forschungsgemeinschaft (DFG) for generously funding this research (WE 1436/12-1), as well as Saskia Bluhm, Marie Reger, and Maximilian Schaedlich for their help in collecting the underlying data.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Institute of Information Systems and Marketing (IISM)Karlsruhe Institute of Technology (KIT)KarlsruheGermany
  2. 2.FZI Forschungszentrum InformatikKarlsruheGermany

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