Overview and outcomes:
Jain and Krishna (2003) provided our theoretical starting point. They are interested in the dynamics of co-evolution and use network theory to explore autocatalytic sets (ACS) which are sets of simple molecular organisms that are unable to self-replicate, but each providing a catalyst for its fellows.
Jain and Krishna use computational models to simulate such a dynamic system. This reveals ‘punctuated equilibria’, with processes of growth and then partial collapse.
The Jain and Krishna model embodies two timescales. The fast (or short) dynamics correspond to fitness propagation within the network; the slow (or long) dynamics correspond to the update and reconfiguration of the network. These features can be interpreted as local innovation (transfer of knowledge between similar technologies) and global innovation (updates to the global technology system).
We apply this model to the study of self-reinforcing processes of social and economic change.
The Jain and Krishna model has attracted a good amount of attention in the literature on complex network dynamics. Nevertheless this is the first and most ambitious attempt to apply their model on a multi-disciplinary basis and with a strong empirical and policy emphasis.
Empirical case studies
Patents: The initial empirical case study is on patents, and we have been given access to the PATSTAT datasets we require. Using the case study of patents as our template, we will extend the research across further social and economic case studies with a view to expanding the mathematical, statistical and empirical scope of the Jain and Krishna model.
Additional case studies are likely to include some of the following:
- Mergers and Acquisitions to track the development and co-evolution of different capabilities in firms
- Financial system to model the co-evolution of risks within connected financial systems
- Welfare regimes to model how institutions concerned with social security, vocational training, employment, etc. co-evolve to produce a number of distinct regimes typical of particular countries
- Developing countries to link science and engineering innovations with the institutional contexts and ‘soft technologies’ of the developing world
- Digital social networks to examine the dynamics of social media, and the insights offered by our modelling for data analytics and digital governance
Research overview, data and papers
We are pleased to make available our research data and first findings on co-evolving systems, technology networks, and innovation patterns.