A Web-Based Political Exchange for Election Outcome Predictions
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
An in-depth analysis of information markets with aggregate uncertainty
Electronic Commerce Research
Supply chain information sharing in a macro prediction market
Decision Support Systems
Negotiation in Technology Landscapes: An Actor-Issue Analysis
Journal of Management Information Systems
Profiling a decade of Information Systems Frontiers' research
Information Systems Frontiers
Information Market-Based Decision Fusion
Management Science
Modeling volatility in prediction markets
Proceedings of the 10th ACM conference on Electronic commerce
Bluffing and strategic reticence in prediction markets
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Proceedings of the 11th ACM conference on Electronic commerce
Decision rules and decision markets
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Prediction Markets as institutional forecasting support systems
Decision Support Systems
Proceedings of the FSE/SDP workshop on Future of software engineering research
Decision markets with good incentives
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
A decision support system for stock investment recommendations using collective wisdom
Decision Support Systems
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Valuations from “prediction markets” reveal expectations about the likelihood of events. “Conditional prediction markets” reveal expectations conditional on other events occurring. For example, in 1996, the Iowa Electronic Markets (IEM) ran markets to predict the chances that different candidates would become the Republican Presidential nominee. Other concurrent IEM markets predicted the vote shares that each party would receive conditional on the Republican nominee chosen. Here, using these markets as examples, we show how such markets could be used for decision support. In this example, Republicans could have inferred that Dole was a weak candidate and that his nomination would result in a Clinton victory. This is only one example of the widespread potential for using specific decision support markets.