Quantitative Identification of Technological Discontinuities

Title
Quantitative Identification of Technological Discontinuities
Author
박현석
Keywords
Knowledge discontinuity; quantitative simulation; knowledge networks; patent citation networks
Issue Date
2019-01
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE ACCESS, v. 7, Page. 8135-8150
Abstract
The aim of this paper is to develop and test the metrics to quantitatively identify technological discontinuities in a knowledge network. We first analyzed the various conceptual frameworks for defining such discontinuities and arrived at four metrics. We tested the four metrics: Metric 1 and 2 are the normalized versions of previously existing metrics and Metric 3 and 4 are newly developed from the innovation theories, by using a patent set representative of the magnetic information storage domain The three representative patents associated with a well-known breakthrough technology in the domain, the giant magneto-resistance spin valve sensor, were selected based on qualitative studies, and the metrics were tested by how well each identifies the selected patents as top-ranked patents. The empirical results show that, first, global citation structure-based metrics clearly provide better performance in the identification of technological discontinuities than local citation count-based metrics which have not been shown as clearly before, second, non-continuous nodes on the major knowledge networks are not at all related to technological discontinuities, and, third, the two global metrics (Metric2: z-score of Persistence and Metric 4: z-score of Persistence times # of converging main paths) successfully identified the three selected patents as top-ranked patents out of over 30 000 patents.
URI
https://ieeexplore.ieee.org/document/8605517http://repository.hanyang.ac.kr/handle/20.500.11754/106135
ISSN
2169-3536
DOI
10.1109/ACCESS.2018.2890372
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > INFORMATION SYSTEMS(정보시스템학과) > Articles
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