Knowledge Networks and Cluster Analysis

Technological invention and scientific research does not readily translate into innovative practice. This is evident in the variance of innovation performance among UK industrial clusters.

Project Background 

In this project we look at the way regional industrial clusters innovate and implement new green technologies. We identify effective innovation dissemination by looking at knowledge creation, as well as the collaboration and patent networks behind it. We map this complex landscape and identify industries where there are opportunities for optimizing the interaction between critical nodes. Of particular interest here is the innovation potential from ties between industry and academia.

We compare these complex network structures between UK industrial regions and highlight best practice in knowledge network clusters. This with particular reference to the knowledge created and disseminated by partners in the IDRIC project. We therefore intend to assess the impact of IDRIC in the creation and dissemination of knowledge.

Research Questions 

  • Identify and compare optimal structures and best innovation practice in UK clusters (including UKRI knowledge transfer partnerships)
  • Identify latent capacity (and any redundancy) in systems of knowledge exchange

Project Lead

Professor Dimitris Christopoulos 

Co-investigators/ PhDs/ RAs 

Research Methods 

Multi-mode network analysis to identify optimal collaboration patterns in innovation networks. Graph matching algorithms to identify the robustness and resilience of knowledge exchange in industrial clusters. We have designed a project that innovatively integrates a group of cogent methods in a mixed methods research design. These take advantage of our expertise and include network analysis, econometric methods, the snowball sampling of expert stakeholders and advanced statistical analysis.