Knowledge creation is widely considered as the central driver for innovation, and accordingly, for creating competitive advantage. However, most measurement approaches have so far mainly focused on the quantitative dimension of knowledge creation, neglecting that not all knowledge has the same value (Balland and Rigby, 2017). The notion of knowledge complexity has come into use in this context just recently as an attempt to measure the quality of knowledge in terms of its uniqueness and its replicability. The central underlying assumption is that more complex knowledge is more difficult to be replicated, and therefore provides a higher competitive advantage for firms, or at an aggregated level, regions and countries. The objective of this study is to advance and apply measures for regional knowledge complexity to a set of European regions, and to highlight its potential in a regional policy context. This is done by, first, characterising the spatial distribution of complex knowledge in Europe and its dynamics in recent years, second, establishing that knowledge complexity is associated with future regional economic growth, and third, illustrating the usefulness of the measures by means of some policy relevant example applications. We proxy the production of complex knowledge with a regional knowledge complexity index (KCI) that is based on regional patent data of European metropolitan regions from current EU and EFTA member countries. The results are promising as the regional KCI unveils knowledge creation patterns not observed by conventional measures. Moreover, regional complexity measures can be easily combined with relatedness metrics to support policy makers in a smart specialisation context.
- Innovation Dynamics and Modelling
- Knowledge complexity ; Technological complexity ; Metropolitan regions ; Patents ; Network analysis