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MInPuD: Method Integration of Prediction Market and Delphi Study

MInPuD：预测市场与德尔菲研究的方法整合

基本信息

批准号：
256547774
负责人：
Professor Dr. Christof Weinhardt
金额：
--
依托单位：
Institut für Wirtschaftsinformatik und Marketing (IISM)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2016-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/256547774?language=en
关键词：
MInPuD Method Integration Prediction Market

项目摘要

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.

全球金融和经济危机中的预测误差只是传统的、基于时间序列的预测方法因突然变化而失败的一个例子。该项目的目标是研究已建立的反馈机制Delphi Study和预测市场的整合是否可以提高总体预测的质量--以及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，目前尚不清楚它们能否很好地处理复杂的相互依赖关系。在任何情况下，它们都允许衡量单个参与者的预测专长。然后，这些参与者可以被邀请并作为德尔福研究的专家进行激励。与预测市场相比，德尔福研究能够得出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。将这两种方法结合起来，同时对整个信息系统进行直观的设计，将大大提高接受度和活跃度，从而提高预测质量。为此，我们将开发一个实时Delphi工具，并将其与现有的EIX预测市场相结合。预测质量的假想改进将在实验室和现场实验中得到检验。用户对集成系统的接受程度将通过扩展技术接受模型进行评估。