Structure of the Region-Technology Network as a Driver for Technological Innovation.

Dion R J O’Neale,Demival Vasques Filho,Shaun C Hendy

doi:10.3389/fdata.2021.689310

Dion R J O’Neale, Demival Vasques Filho + Show 1 more

Open Access

https://doi.org/10.3389/fdata.2021.689310

Copy DOI

Abstract

Agglomeration and spillovers are key phenomena of technological innovation, driving regional economic growth. Here, we investigate these phenomena through technological outputs of over 4,000 regions spanning 42 countries, by analyzing more than 30 years of patent data (approximately 2.7 million patents) from the European Patent Office. We construct a bipartite network—based on revealed comparative advantage—linking geographic regions with areas of technology and compare its properties to those of artificial networks using a series of randomization strategies, to uncover the patterns of regional diversity and technological ubiquity. Our results show that the technological outputs of regions create nested patterns similar to those of ecological networks. These patterns suggest that regions need to dominate various technologies first (those allegedly less sophisticated), creating a diverse knowledge base, before subsequently developing less ubiquitous (and perhaps more sophisticated) technologies as a consequence of complementary knowledge that facilitates innovation. Finally, we create a map—the Patent Space Network—showing the interactions between technologies according to their regional presence. This network reveals how technology across industries co-appear to form several explicit clusters, which may aid future works on predicting technological innovation due to agglomeration and spillovers.

Highlights

Innovation is facilitated by the combination of diverse yet complementary knowledge inputs (Jacobs, 1969)
The value of adding an additional technology to a set of pre-existing capabilities will vary depending on both the new technology and the existing combination. This would suggest that those regions with a diverse knowledge base are at an advantage when it comes to regional technological progress (Feldman and Audretsch, 1999)
The triangular structure indicates that the technologies associated with inventions from low diversity regions tend to be subsets of those used by high diversity regions. This structure indicates that the Ricardian model of producing goods for trade does not apply here, if we were to extrapolate the model for the production of technology. Such a model for technological production would lead to an adjacency matrix with a block-diagonal structure as regions would specialize in only those technologies that they have a comparative advantage for and which will have the lowest ubiquity, at the expense of having high diversity through producing some more ubiquitous technologies

Summary

Introduction

Innovation is facilitated by the combination of diverse yet complementary knowledge inputs (Jacobs, 1969). Some of the most influential conceptualisations of the innovation process regard technological change as originating from the combination of new and existing technological capabilities (Weitzman, 1998). The value of adding an additional technology to a set of pre-existing capabilities will vary depending on both the new technology and the existing combination. This would suggest that those regions with a diverse knowledge base are at an advantage when it comes to regional technological progress (Feldman and Audretsch, 1999)

Methods

Results

Conclusion