Abstract
In-house prediction markets are a new method for collecting and aggregating information dispersed throughout an organization. This method is capable of accessing and aggregating certain organizational information that has previously not been attainable via traditional methods such as surveys, polls, group meetings, or suggestion boxes. Such information is often of great tactical and/or strategic value. Existing in-house prediction markets, which are either opened to all members of the organization or to pre-selected groups of experts within the organization, base participant’s power to influence the market strictly on the amount of their assets (usually in mock currency). We propose a more nuanced design approach that considers additional factors for determining the participant’s influence on the market over the long term. The goal of this design approach is to improve the accuracy and decision-support viability of in-house prediction markets.
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Velacso, M., Jukic, N. (2010). A Framework for In-House Prediction Markets. In: Zavoral, F., Yaghob, J., Pichappan, P., El-Qawasmeh, E. (eds) Networked Digital Technologies. NDT 2010. Communications in Computer and Information Science, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14292-5_13
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DOI: https://doi.org/10.1007/978-3-642-14292-5_13
Publisher Name: Springer, Berlin, Heidelberg
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