“Learning Hubs” on the Global Innovation Network

Abstract

In this paper, drawing on techniques from patentometrics, network analysis, and probability theory, we model the global system of innovation as a dynamic network. The sphere of technologically relevant knowledge is conceptualized as a reflexive, directed, link- and node-weighted complex network, with distinct spheres of knowledge (or technology domains) representing network nodes and learning (or knowledge flows) across domains acting as inter-nodal links. The empirical knowledge network is constructed from a sweeping patent database, including records from more than 100 patent-granting authorities over the 22-year period spanning 1991–2012. After establishing the structure of the global innovation network, we simulate its dynamics and study its evolution over time. The modelling exercise reveals technological trends and provides a ranking of technologies in terms of their level of technological dynamism.