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Using structural diversity to measure the complexity of technologies

The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argu...

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Detalles Bibliográficos
Autor principal: Broekel, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528977/
https://www.ncbi.nlm.nih.gov/pubmed/31112571
http://dx.doi.org/10.1371/journal.pone.0216856
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author Broekel, Tom
author_facet Broekel, Tom
author_sort Broekel, Tom
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description The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argued that this measure can be empirically approximated with the Network Diversity Score (NDS). The paper also presents an application of this approach to European patent data from 1980 to 2015. On this basis, the measure of structural diversity is shown to replicate a number of stylized facts commonly associated with technological complexity: Complexity increases over time and younger technologies are more complex than older technologies. Complex technologies are also associated to larger R&D efforts and require more collaborative R&D activities. Lastly, when controlling for technologies’ size, technologies scoring high on structural diversity are also shown to concentrate in space.
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spelling pubmed-65289772019-05-31 Using structural diversity to measure the complexity of technologies Broekel, Tom PLoS One Research Article The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argued that this measure can be empirically approximated with the Network Diversity Score (NDS). The paper also presents an application of this approach to European patent data from 1980 to 2015. On this basis, the measure of structural diversity is shown to replicate a number of stylized facts commonly associated with technological complexity: Complexity increases over time and younger technologies are more complex than older technologies. Complex technologies are also associated to larger R&D efforts and require more collaborative R&D activities. Lastly, when controlling for technologies’ size, technologies scoring high on structural diversity are also shown to concentrate in space. Public Library of Science 2019-05-21 /pmc/articles/PMC6528977/ /pubmed/31112571 http://dx.doi.org/10.1371/journal.pone.0216856 Text en © 2019 Tom Broekel http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Broekel, Tom
Using structural diversity to measure the complexity of technologies
title Using structural diversity to measure the complexity of technologies
title_full Using structural diversity to measure the complexity of technologies
title_fullStr Using structural diversity to measure the complexity of technologies
title_full_unstemmed Using structural diversity to measure the complexity of technologies
title_short Using structural diversity to measure the complexity of technologies
title_sort using structural diversity to measure the complexity of technologies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528977/
https://www.ncbi.nlm.nih.gov/pubmed/31112571
http://dx.doi.org/10.1371/journal.pone.0216856
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