Rapidly changing economic and environmental conditions require regions to continuously adapt and re-invent themselves by developing new areas of scientific and technological excellence. During the past two decades, the geography of innovation literature has provided a rich and detailed account of the underlying processes of regional knowledge production. We know relatively well why some regions produce more knowledge outputs than others, but how do regions develop specific areas of scientific and technological excellence? In this paper I ask two main questions: what do we know about technological diversification of regions? And what kind of lessons can we draw for regional innovation policy? The analytical framework I use to answer these questions is based on evolutionary thinking, in which the spatial dynamics of knowledge is understood as a cumulative, path-dependent and interactive process. As a result, a main driving force is relatedness, as new knowledge is expected to branch out from related, pre-existing knowledge. I provide a critical assessment of the recent empirical literature that has analyzed technological diversification of regions - in which the concept of relatedness has mainly been formalized as a network (knowledge space). In this network, nodes are knowledge categories, such as technological classes or scientific fields, and the links between these knowledge types indicate their degree of relatedness. In an attempt to contribute to the smart specialization debate I discuss how this framework can be used to map knowledge bases of regions, predict regional scientific and technological change, and identify further opportunities for recombination and innovation.
Technological diversification of regions: theory, empirics, and policy
Feb 11th, 2016
Pierre-Alexandre Balland (Utrecht University)