Abstract:
Innovation and technological change play an important role in theories of endogenous economic growth. Yet current models do not explain the specialisation of countries and regions, and why these regions experience different rates of growth. The availability of large data sets relevant to scientific and technological innovation, such as patent and publication records, allow us to make use of complex systems and network science approaches, and to take a data analytic approach to innovation. We describe several recent approaches, which can be used to gain insight into scientific innovation and its economic effects, before presenting "patent space" ‐ a network representation of regionalised patent records that allows analysis of patentable innovation. Examples showing national, regional and temporal effects in innovation are used to illustrate the use of the technique.