MInPuD: Method Integration of Prediction Market and Delphi Study

全球金融和经济危机的预测误差只是传统的基于时间序列的预测方法在突变情况下失败的一个例子。本项目的目的是研究将已建立的反馈机制德尔菲研究与预测市场相结合，是否可以提高总体预测的质量，以及在其他应用场景中对经济指标的预测。众所周知，预测市场是预测简单事件的有力工具。然而，它们如何处理复杂的相互依赖关系尚不清楚。在任何情况下，它们允许测量个体参与者的预测专业知识。然后可以邀请这些参与者并激励他们成为德尔菲研究的专家。德尔菲研究能够引出比预测市场更复杂的信息设置和相互依赖关系。因此，它们可以定性地支持基于市场的预测。两种方法的集成以及整体信息系统的直观设计将导致接受度和活动的大幅增加，从而提高预测质量。为此，我们将开发一个实时Delphi工具，并将其与已建立的EIX预测市场相结合。预测质量的改善将在实验室和现场实验中进行测试。用户对集成系统的接受程度将通过扩展的技术接受模型进行评估。

Prediction errors in the global financial and economic crises are but one example for the failure of traditional, time-series-based prediction methods in the light of abrupt changes. The objective of this project is studying whether the integration of the established feedback mechanisms Delphi study and prediction market can improve the quality of predictions in general -- and among other application scenarios the forecasting of economic indicators. It is well known that prediction markets are potent tools to forecast simple events. It is, however, not known how well they can handle complex interdependencies. In any case, they allow for measuring the prediction expertise of individual participants. These participants can then be invited and incentivized as experts in a Delphi study. Delphi studies are able to elicit more complex information settings and interdependencies than prediction markets. Thereby, they can qualitatively support market-based predictions. An integration of both methods alongside an intuitive design of the overall information system will result in a substantial increase in acceptance and activity and thereby improve prediction quality. To this end, we will develop a real-time Delphi tool and integrate it with the established EIX prediction market. The hypothesized improvement in prediction quality will be tested in laboratory and field experiments. Users' acceptance of the integrated system will be evaluated via extended Technology Acceptance Models.