Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박현석 | - |
dc.date.accessioned | 2020-08-27T04:42:57Z | - |
dc.date.available | 2020-08-27T04:42:57Z | - |
dc.date.issued | 2019-08 | - |
dc.identifier.citation | PLOS ONE, v. 14, NO. 8, article no. e0220819 | en_US |
dc.identifier.issn | 1932-6203 | - |
dc.identifier.uri | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220819 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/152646 | - |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning (No. 2017R1A2B4012431). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. | en_US |
dc.language.iso | en | en_US |
dc.publisher | PUBLIC LIBRARY SCIENCE | en_US |
dc.subject | DOMINANT DESIGNS | en_US |
dc.subject | TRAJECTORIES | en_US |
dc.subject | PATENTS | en_US |
dc.subject | NETWORKS | en_US |
dc.subject | NOVELTY | en_US |
dc.subject | SEARCH | en_US |
dc.title | Quantitative identification of technological paradigm changes using knowledge persistence | en_US |
dc.type | Article | en_US |
dc.relation.no | 8 | - |
dc.relation.volume | 14 | - |
dc.identifier.doi | 10.1371/journal.pone.0220819 | - |
dc.relation.page | 1-16 | - |
dc.relation.journal | PLOS ONE | - |
dc.contributor.googleauthor | Mun, Changbae | - |
dc.contributor.googleauthor | Yoon, Sejun | - |
dc.contributor.googleauthor | Kim, Yongmin | - |
dc.contributor.googleauthor | Raghavan, Nagarajan | - |
dc.contributor.googleauthor | Park, Hyunseok | - |
dc.relation.code | 2019042142 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF INFORMATION SYSTEMS | - |
dc.identifier.pid | hp | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.