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Quantitative identification of technological paradigm changes using knowledge persistence

This paper proposes a method to quantitatively identify the changes of technological paradigm over time. Specifically, the method identifies previous paradigms and predicts future paradigms by analyzing a patent citation-based knowledge network. The technological paradigm can be considered as domina...

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Detalles Bibliográficos
Autores principales: Mun, Changbae, Yoon, Sejun, Kim, Yongmin, Raghavan, Nagarajan, Park, Hyunseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695126/
https://www.ncbi.nlm.nih.gov/pubmed/31415621
http://dx.doi.org/10.1371/journal.pone.0220819
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author Mun, Changbae
Yoon, Sejun
Kim, Yongmin
Raghavan, Nagarajan
Park, Hyunseok
author_facet Mun, Changbae
Yoon, Sejun
Kim, Yongmin
Raghavan, Nagarajan
Park, Hyunseok
author_sort Mun, Changbae
collection PubMed
description This paper proposes a method to quantitatively identify the changes of technological paradigm over time. Specifically, the method identifies previous paradigms and predicts future paradigms by analyzing a patent citation-based knowledge network. The technological paradigm can be considered as dominantly important knowledge in a specific period. Therefore, we adopted the knowledge persistence which can quantify technological impact of an invention to recent technologies in a knowledge network. High knowledge persistence patents are dominant or paradigmatic inventions in a specific period and so changes of top knowledge persistence patents over time can show paradigm shifts. Moreover, since knowledge persistence of paradigmatic inventions are increasing dramatically faster than other ordinary inventions, recent patents having similar increasing trends in knowledge persistence with previous paradigms are identified as future paradigm inventions. We conducted an empirical case study using patents related to the genome sequencing technology. The results show that the identified previous paradigms are widely recognized as critical inventions in the domain by other studies and the identified future paradigms are also qualitatively significant inventions as promising technologies.
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spelling pubmed-66951262019-08-16 Quantitative identification of technological paradigm changes using knowledge persistence Mun, Changbae Yoon, Sejun Kim, Yongmin Raghavan, Nagarajan Park, Hyunseok PLoS One Research Article This paper proposes a method to quantitatively identify the changes of technological paradigm over time. Specifically, the method identifies previous paradigms and predicts future paradigms by analyzing a patent citation-based knowledge network. The technological paradigm can be considered as dominantly important knowledge in a specific period. Therefore, we adopted the knowledge persistence which can quantify technological impact of an invention to recent technologies in a knowledge network. High knowledge persistence patents are dominant or paradigmatic inventions in a specific period and so changes of top knowledge persistence patents over time can show paradigm shifts. Moreover, since knowledge persistence of paradigmatic inventions are increasing dramatically faster than other ordinary inventions, recent patents having similar increasing trends in knowledge persistence with previous paradigms are identified as future paradigm inventions. We conducted an empirical case study using patents related to the genome sequencing technology. The results show that the identified previous paradigms are widely recognized as critical inventions in the domain by other studies and the identified future paradigms are also qualitatively significant inventions as promising technologies. Public Library of Science 2019-08-15 /pmc/articles/PMC6695126/ /pubmed/31415621 http://dx.doi.org/10.1371/journal.pone.0220819 Text en © 2019 Mun et al 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
Mun, Changbae
Yoon, Sejun
Kim, Yongmin
Raghavan, Nagarajan
Park, Hyunseok
Quantitative identification of technological paradigm changes using knowledge persistence
title Quantitative identification of technological paradigm changes using knowledge persistence
title_full Quantitative identification of technological paradigm changes using knowledge persistence
title_fullStr Quantitative identification of technological paradigm changes using knowledge persistence
title_full_unstemmed Quantitative identification of technological paradigm changes using knowledge persistence
title_short Quantitative identification of technological paradigm changes using knowledge persistence
title_sort quantitative identification of technological paradigm changes using knowledge persistence
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695126/
https://www.ncbi.nlm.nih.gov/pubmed/31415621
http://dx.doi.org/10.1371/journal.pone.0220819
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