Prediction Markets as an Innovative Way to Manage R&d Portfolios

R&D portfolio management is a critical task with which the majority of the large companies are confronted. Despite its wide implementation in companies there are no widely accepted and used methods to perform this task. Each company uses its own mix of various qualitative and quantitative methods to achieve its goal. The objective of this thesis is to explore the adequacy and the design issues to use a prediction market for supporting the R&D portfolio management process. We chose prediction markets to perform this task since their aggregation mechanisms and information discovery process seems to solve most of the current issues of the R&D portfolio management process.