Theory of human enterprise

Developing mathematical models of markets, innovation and organisations, so that we can predict them and enhance them through interventions.

Science has traditionally been concerned with the natural world. But as society gets more interconnected and organisations get larger, the man-made world needs a science of its own.

Despite advances in our understanding of evolution, what drives innovation remains elusive. Technological innovation operates in an expanding space of building blocks, in which combinations of technologies become new technologies. Can we characterise innovation in a mathematical way, so that we can predict and influence it?

Anonymous collaboration platforms, such as Wikipedia, suggest that many non-interacting people can achieve creative acts superior to what any one person could do alone. But why and when does collective creativity work? Can platforms like Gowers’ Polymath transform the process of discovery?

The sentiment of borrowers and lenders in a financial network is what drives markets to success, but also to ruin. Zooming in on the non-linear links between these players quantifies the likely reactions to key events, and predicts how distress will spread. What strategies could limit system-wide catastrophic failure, and prevent future existential crises?

  • A fix for failure that’s contagious

    Systemic risk

    Applying ideas from diversification and cascading failures to mitigate the propagation of risk across inter-connected institutions.

  • Economic complexity

    Applying spectral-like theories to the bipartite network of products and capabilities to find latent potential in countries and firms.

  • Hidden communities

    Employing theoretical measures to detect communities and connections in complex networks.

  • Sense from social networks

    Developing new local and global measures for networks derived from social interactions to infer social structure, sentiment and behaviour.

  • Markets and the mind

    Examining the effect of public opinion on stock market returns and harnessing social sentiment to make quantitative market predictions.

  • News and fake news

    Investigating the adverse effects of information asymmetry and deliberate errors in social media and the press, and attempts to remedy them.

  • Reconstructing credit networks

    Using ideas from statistical physics to reconstruct the average properties of financial networks from partial sets of information.

  • Repairable instead of robust

    Developing a new approach to resilience in which mistakes and unexpected events are mitigated by easy repairs rather than redundancy.

  • Technological progress

    Forecasting the rate of technological progress by harnessing empirical regularities captured by Moore’s law and Wright’s law.

  • The structure of innovation

    Creating a mathematical model of combinatorial innovation to understand how innovation rates can be influenced as components are acquired.