LQ placeholderMathematical structure of innovation

Mathematical structure of innovation

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

Background Innovation is to technology what evolution is to life: it is how technology improves and adapts to changing needs and environments. Yet despite advances in our understanding of evolution, what drives innovation has remained elusive. Is the innovation process essentially Darwinian—mutation, selection and inheritance—or are there fundamentally different rules at play?

Project We develop a simple mathematical model of innovation in which technologies are made up of components and new components become available over time. While the choices that organizations make play an important role in determining their success, this is countered by an intrinsic innovation rate specific to each domain. These opposing forces are reminiscent of nurture versus nature in human traits.

Consequences Mathematical models can help structure our empirical investigation of innovation in the real world, and better capture the intrinsic versus intervenable aspects of technological change. The ability to influence the rate of innovation in sectors such as energy production, software development and drug discovery will have enormous benefits for sustainability, technological progress and the health of the nation.

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