The notion of ‘Knowledge Society’ signifies the importance of knowledge today. Our view is that knowledge and learning are the main, if not the only, sources of competitiveness for organisations.
In order to help organisations make better use of this exceptionally important source, our research group covers a wide range of knowledge modelling.
At the most conceptual level, we're exploring the fundamentals of knowledge, problems, creativity, intuition, levels of expertise, risk, perception of risk, and subjective probabilities.
We do most of our work in applied contexts, structuring problems and modelling expert knowledge in order to support decision makers and decision takers in their organisations. Our research also served as basis for developing a number of software packages used for knowledge modelling.
Our research projects
- Grandmaster project
- Expert judgement network: Bridging the gap between scientific uncertainty & evidence-based decision making
- Expert judgement & reliability
Academic staff active in this area may be available for supervising PhDs or collaboration on the following topics:
Viktor's interested in both empirical and conceptual research of knowledge and learning at personal, transpersonal, and organisational levels. He's also interested in knowledge modelling with knowledge-based expert systems (KBS), sometimes also referred to as knowledge-based decision support system (kbDSS).
Tim's interested in combining fundamental theoretical advances of risk analysis – particularly around probability and consequence modelling – with applications to real-life problems.
Professor Val Belton
Val's interested in Multicriteria Decision Analysis (MCDA), from both conceptual and applied perspectives. She also looks at integrating MCDA with a range of different methods, such as cognitive mapping, system dynamics, and discrete event simulation.
Software packages based on the work of this research group include:
For general enquiries about the knowledge research group please contact Dr Viktor Dörfler.