Models of Complexity

Complexity science is not a social science, but it offers mental models that innovative thinkers in academia, business, and government can use as a reference to model real-world complex economic, political, social and business situations. Thinking carefully about the multiscale, interconnected, evolving complex systems that upset humankind today —the economy, our food supply, sustainability, urban development, the power grid, technological innovation, to name a few— demands tools, approaches, and modes of problem solving that transcend the narrow domains of individual, specialized fields. A complexity thinker needs not be a mathematician, a biologist, or a physicist to apply fresh perspectives to chronic or highly complex problems, but she can take comprehensive approach to the problems she wishes to tackle. For instance, theories of scaling from biology can be helpful to explain how cities and firms grow and approaches from network science provide deep insights about the workings of companies and commerce, the nature of human social relationships, and the functioning of social networks. On the other hand, the careful study of economic and social phenomena can contribute to the development of Complexity Science. For example, the analysis of the demography of cities requires an approach capable to model a system of systems where each city interacts with other cities in the all-encompassing system of a country.

Research projects:

  1. Self-organization, complexity and system dynamics.
  2. Self-organization of firms.
  3. Self-organization of cities.
  4. Factors and dynamics of the growth of firms.
  5. Factors and dynamics of the growth of cities.

Project participants:

Fernando Buendía.
Ignacio Martíne-Moyano.

« Back to Research