- Information Systems Modeling and Design
- Technological Forecasting
- Decision Science (Decision Support Systems)
- Data Science
- Green IS
My primary research focus has been on prediction markets, which are speculative markets created for the purpose of making predictions. Shares are created whose final cash value is tied to a particular event or parameter. The current market prices can then be interpreted as predictions of the probability of the event or the expected value of the parameter. This emerging research topic has not been extensively studied in an information systems perspective. Previous research indicates that there was a need to study the design of prediction markets for enterprise applications. Therefore, new experiments and architectures had to be designed. My dissertation proposes tackling new enterprise prediction markets applications using a design science approach. We developed and instantiated three prediction markets to support R&D portfolio management, technological forecasting and idea evaluation. This led us to define various design properties, considering the application field and the expected outcomes. Most of my publications are directly related to this topic.
In the short time I have been doing research in the prediction market field, I have become an expert in enterprise prediction markets by both academia and industry. This resulted in many invited talks, as well as numerous apparitions in public radio broadcasts and newspapers. My contributions are both theoretical and practical. Importantly, I was able to find a good balance between rigor and relevance, one of the major challenges in the current information systems research community.
In terms of theoretical contributions, we demonstrated the successful use of prediction markets to support R&D portfolio management and technology foresight, two new prediction markets applications. Therefore, we established a comparison framework for technology foresight applications and compared prediction markets with more traditional approaches like MCDM. We also drafted an ontology based method to support the design requirements on a business perspective. In terms of practical implications, we developed a set of design recommendations to develop and run such markets in a corporate environment.
My future research plans are to strengthen the current progress I have made within the prediction markets and decision support systems fields. There are many aspects of these topics that emerged during my dissertation like requirements engineering, information aggregation and retrieval, green IS.
In an attempt to support the design of corporate prediction markets, we drafted an ontology based requirement analysis. Such a method could greatly improve the use of DSS tools in enterprise and would support a broad range of applications, allowing managers to dynamically create and adapt their application’s requirements, based on their business needs.
Furthermore, we found that in order to support technological forecasting we should improve the creation of new shares on prediction markets. We are currently conducting exploratory research with Prof. Falquet, using classificators on large datasets to extract emerging research topics. The next step would be to explore the use of ontology and web semantic to improve the work done by the classificators, allowing the creation of prediction markets’ shares based on the extracted emerging research fields.
Finally, in a DSS approach, we started studying the impact of IS on sustainable development. In the emerging field of Green IS, initiated by Prof. Watson, there are a lot of opportunities for research on corporate DSS to support companies on their transition to more sustainability. We started an interesting research on the impact of DSS on individual mobility, accompanying a new bike sharing project in Switzerland. Our research assumption is that prediction markets are appropriate tools to support the ideation process of company becoming greener.