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Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network †
In this work we aim at identifying combinations of technological advancements that reveal the presence of local capabilities for a given industrial production. To this end, we generated a multilayer network using country-level patent and trade data, and performed motif-based analysis on this network...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514614/ https://www.ncbi.nlm.nih.gov/pubmed/33266842 http://dx.doi.org/10.3390/e21020126 |
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author | Formichini, Martina Cimini, Giulio Pugliese, Emanuele Gabrielli, Andrea |
author_facet | Formichini, Martina Cimini, Giulio Pugliese, Emanuele Gabrielli, Andrea |
author_sort | Formichini, Martina |
collection | PubMed |
description | In this work we aim at identifying combinations of technological advancements that reveal the presence of local capabilities for a given industrial production. To this end, we generated a multilayer network using country-level patent and trade data, and performed motif-based analysis on this network using a statistical-validation approach derived from maximum-entropy arguments. We show that in many cases the signal far exceeds the noise, providing robust evidence of synergies between different technologies that can lead to a competitive advantage in specific markets. Our results can be highly useful for policymakers to inform industrial and innovation policies. |
format | Online Article Text |
id | pubmed-7514614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75146142020-11-09 Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † Formichini, Martina Cimini, Giulio Pugliese, Emanuele Gabrielli, Andrea Entropy (Basel) Article In this work we aim at identifying combinations of technological advancements that reveal the presence of local capabilities for a given industrial production. To this end, we generated a multilayer network using country-level patent and trade data, and performed motif-based analysis on this network using a statistical-validation approach derived from maximum-entropy arguments. We show that in many cases the signal far exceeds the noise, providing robust evidence of synergies between different technologies that can lead to a competitive advantage in specific markets. Our results can be highly useful for policymakers to inform industrial and innovation policies. MDPI 2019-01-30 /pmc/articles/PMC7514614/ /pubmed/33266842 http://dx.doi.org/10.3390/e21020126 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Formichini, Martina Cimini, Giulio Pugliese, Emanuele Gabrielli, Andrea Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † |
title | Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † |
title_full | Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † |
title_fullStr | Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † |
title_full_unstemmed | Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † |
title_short | Influence of Technological Innovations on Industrial Production: A Motif Analysis on the Multilayer Network † |
title_sort | influence of technological innovations on industrial production: a motif analysis on the multilayer network † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514614/ https://www.ncbi.nlm.nih.gov/pubmed/33266842 http://dx.doi.org/10.3390/e21020126 |
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