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

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 pate...

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Autores principales: O’Neale, Dion R. J., Hendy, Shaun C., Vasques Filho, Demival
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316829/
https://www.ncbi.nlm.nih.gov/pubmed/34337398
http://dx.doi.org/10.3389/fdata.2021.689310
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author O’Neale, Dion R. J.
Hendy, Shaun C.
Vasques Filho, Demival
author_facet O’Neale, Dion R. J.
Hendy, Shaun C.
Vasques Filho, Demival
author_sort O’Neale, Dion R. J.
collection PubMed
description 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.
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spelling pubmed-83168292021-07-29 Structure of the Region-Technology Network as a Driver for Technological Innovation O’Neale, Dion R. J. Hendy, Shaun C. Vasques Filho, Demival Front Big Data Big Data 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. Frontiers Media S.A. 2021-07-14 /pmc/articles/PMC8316829/ /pubmed/34337398 http://dx.doi.org/10.3389/fdata.2021.689310 Text en Copyright © 2021 O’Neale, Hendy and Vasques Filho. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
O’Neale, Dion R. J.
Hendy, Shaun C.
Vasques Filho, Demival
Structure of the Region-Technology Network as a Driver for Technological Innovation
title Structure of the Region-Technology Network as a Driver for Technological Innovation
title_full Structure of the Region-Technology Network as a Driver for Technological Innovation
title_fullStr Structure of the Region-Technology Network as a Driver for Technological Innovation
title_full_unstemmed Structure of the Region-Technology Network as a Driver for Technological Innovation
title_short Structure of the Region-Technology Network as a Driver for Technological Innovation
title_sort structure of the region-technology network as a driver for technological innovation
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316829/
https://www.ncbi.nlm.nih.gov/pubmed/34337398
http://dx.doi.org/10.3389/fdata.2021.689310
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