Research methodology

In addition to improving fundamental understanding of organisational knowledge and information dynamics and its role in organizational processes such as knowledge creation and innovation, this research will allow to understand the structure and behaviour of complex hierarchical socio-technological systems. To fulfil the research goals, the project will focus on a comprehensive set of theoretical, methodological and experimental research activities driven by application of systems thinking perspective in multi- and inter-disciplinary environment of socio-technical systems. The focus of the research activities will be to cover the creation and analysis of complex systems models including identifying what is to be modelled, constructing a mathematical representation, and development of simulation and analyse tools.

The research methodology will be accompanied with series of presentations/lectures, experimental work, and discussion sessions focusing on foundational ideas, methods, tools, and current topics in complex systems research with the focus to the organisational knowledge.

Scientific methods that will be applied during the research project include: statistical methods, social and dynamic network analysis, agent - based modelling and pattern recognition. Among the others, research group members will be trained to use multi-scale representations based on the graph theory as a unifying approach to complex systems concepts, methods and applications with the focus to the key properties of the complex systems: emergence, self-organization, motifs formation, evolution, adaptation, cooperation, competition, interdependence, scaling and dynamic response.

Tools developed during the research will facilitate quantitative or qualitative analysis of complex networks, describing features through numerical or visual representation. The models and tools will be used to perform predictive analysis of network outcomes such as the formation of a tie/edge using existing network phenomena to estimate future innovation dynamics in observed socio-technological networks.