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http://dx.doi.org/10.15207/JKCS.2021.12.7.207

Research on the type of technology convergence in the medical device industry based on topic modeling and citation analysis  

Lee, Seonjae (Department of Industrial Engineering, Ajou University)
Lee, Sungjoo (Department of Industrial Engineering, Ajou University)
Seol, Hyeonju (School of Integrated National Security, Chungnam National University)
Publication Information
Journal of the Korea Convergence Society / v.12, no.7, 2021 , pp. 207-220 More about this Journal
Abstract
Industrial convergence is manifested in various forms by various drivers, and understanding and categorizing the direction of convergence according to the factors in which the convergence occurs is an essential requirement for the establishment of a company's customized convergence strategy and the government's corporate support policy. In this study, the type of convergence is analyzed from the perspective of knowledge flow between heterogeneous technologies, and for this purpose, the result of topic modeling of the text information of the patent and the citation information of the corresponding patent allocated for each topic are used. The methodology presented through case studies in the medical device field is verified. Through the proposed methodology, companies can predict the flow of convergence and use it as decision-making data to create new business opportunities. It is expected that the government and research institutions will be usefully used as basic data for policy preparation.
Keywords
Technology convergence; Convergence typology; Topic modeling; Citation analysis; Medical device;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 H. J. Kang & K. G. Kim. (2007). A Study on Impacts of Industrial Convergence Using Patent Citation. Journal of Technology Innovation, 22(2), 31. https://doi.org/10.14383/SIME.2014.22.2.031   DOI
2 T. K. Kim, H. R. Choi & H. C. Lee. (2016). A Study on the Research Trends in Fintech using Topic Modeling. Journal of the Korea Academy Industrial Cooperation Society, 17(11), 670-681. https://doi.org/10.5762/KAIS.2016.17.11.670   DOI
3 M. Steyvers & T. Griffiths. (2007). Probabilistic Topic Models. Handbook of latent semantic analysis, 427(7), 424-440.
4 B. K. Jeong, J. W. Kim & J. H. Yoon. (2016). A Semantic Patent Analysis Approach to Identifying Trends of Convergence Technology: Application of Topic Modeling and Cross-impact Analysis, The Journal of Intellectual Property, 1(4), 21-240. http://dx.doi.org/10.34122/jip.2016.12.11.4.211   DOI
5 J. H. Lee, I. S. Lee, K. S. Jung, B. H. Chae & J. Y. Lee. (2017). Patents and Papers Trends of Solar-Photovoltaic(PV) Technology using LDA Algorithm. Journal of Digital Convergence, 15(9), 231-239. http://dx.doi.org/10.14400/JDC.2017.15.9.231   DOI
6 D. M. Blei, A. Y. Ng & M. I. Jordan. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3, 993-1022.
7 T. Griffiths & M. Steyvers. (2004). Finding Scientific Topics. Proceedings of the National Academy of Sciences, 101(1), 5228-5235.   DOI
8 K. C. Nam, H. C. Kim & B. S. Kwon. (2014). ICT Convergence Medical Device. The Journal of The Korean Institute of Communication Sciences, 31(12), 44-50.
9 G. T. Song & S. J. Song. (2018). Recent research trends in smart medical devices and ICT convergence medical industry. The Journal of The Korean Institute of Communication Sciences, 35(6), 50-55.
10 K. R. Lee. (2015). Toward a new paradigm of technological innovation: convergence innovation. Asian Journal of Technology Innovation, 23, 1-8. https://doi.org/10.1080/19761597.2015.1019226   DOI
11 FDA. (2016). Postmarket Management of Cybersecurity in Medical Devices.
12 J. H. Yoon & K. S. Kim. (2011). A Study on Interdisciplinary Trends of Technological Convergence Using Patent Information: The Case of Air Pollutant Control Technology. Entrue Journal of Information Technology 10(2), 21.
13 Y. J. Geum, M. S. Kim & S. J. Lee. (2016). How industrial convergence happens: A taxonomical approach based on empirical evidences. Technological Forecasting and Social Change, 107, 112-120. https://doi.org/10.1016/j.techfore.2016.03.020   DOI
14 B. G. Jeong, J. W. Kim & J. H. Yun. (2015). Patent-based competitive intelligence analysis of augmented reality technology : Application of topic modeling". The Korean Institute of Industrial Engineers 2015 Conference, 2265-2270.
15 S. H. Park, Y. J. Choi, S. J. Lee & H. J. Seol. (2020). Analysis of Technology Convergence by an Integrated Use of Dynamic Topic Modeling and Network Analysis :ICT-Agritech Case. Journal of the Korean Institute of Industrial Engineers, 46(3), 21-21. DOI : 10.7232/JKIIE.2020.46.3.211   DOI
16 J. S. Park, S. G. Hong & J. W. Kim. (2017). A Study on Science Technology Trend and Prediction Using Topic Modeling. Journal of the Korea Industrial Information Systems Research, 22(4), 19-28. https://doi.org/10.9723/jksiis.2017.22.4.019   DOI
17 K. B. Kim & K. H. Han. (2020). A Study of the Digital Healthcare Industry in the Fourth Industrial Revolution. Journal of Convergence for Information Technology, 10(3), 7-15. https://doi.org/10.22156/CS4SMB.2020.10.03.007   DOI
18 D. W. Kim. (2021). A Study on the Smart Medical Equipment Management Program (Secure-MEMP) Method Considering Securit. Jouranl of Information and Security, 21(1), 63-72.   DOI
19 N. Y. Han & J. B. Hong. (2012). Convergence Types of Smal and Medium Companies Understod Through Convergence Research Development. Asia-Pacific Journal of Business Venturing and Entrepreneurship, 7(2), 19-24. http://dx.doi.org/10.16972/apjbve.7.2.201207.19   DOI
20 W. Xing, X. Ye & L. Kui. (2011). Measuring convergence of China's ICT industry : an input-output analysis. Telecommunications Policy, 35(4), 301-313. https://doi.org/10.1016/j.telpol.2011.02.003   DOI
21 H. J. Kang, M. J. Um & D. M. Lim. (2006), A Study on Forecast of the Promising Fusion Technology by US Patent Analysis, Technology Innovation Research, 14(3), 93-116.
22 S. H. Lee & J. Y. Kim. (2020). Artificial intelligence technology trend based on medical big data. The Journal of The Korean Institute of Communication Sciences, 37(9), 85-91.
23 S. H. Park, Y. M. Yun, H. Y. Kim & J. S. Kim. (2021). Technology Convergence & Trend Analysis of Biohealth Industry in 5 Countries : Using patent co-classification analysis and text mining. Journal of the Korea Convergence Society, 12(4), 9-21.   DOI
24 S. Rhoades. (1993). The Herfindahl-Hirschman Index. Federal Reserve Bulletin, 79(3), 188-9.
25 Y. R. Cho & E. S. Kim. (2014). A Corporate Strategy on Technological Convergence through Analyzing Patent Networks and Strategic Indicators. The Journal of Intellectual Property, 9(4), 191-221. http://dx.doi.org/10.34122/jip.2014.12.9.4.191   DOI
26 C. Curran & J. Leker. (2011). Patent indicators for monitoring con vergence-examples from NFF and ICT. Technological Forecasting and Social Change, 78(2), 256-273. https://doi.org/10.1016/j.techfore.2010.06.021   DOI
27 Y. S. Park, W. H. Shon, S. M. Cho & H. J. Lee. (2013). Study for Industrial Convergence Degree Analysis Method based on Industrial Convergence Type. Korean Society for Precision Engineering 2013 Conference, 1289-1290.
28 F. Hacklin, C. Marxt & F. Fahrni. (2009). Coevolutionary cycles of convergence: an extrapolation from the ICT industry. Technological Forecasting and Social Change, 76(6), 723-736. https://doi.org/10.1016/j.techfore.2009.03.003   DOI
29 B. P. Abraham & S. D. Moitra. (2001). Innovation assessment through patent analysis. Technovation, 21(4), 245-252. https://doi.org/10.1016/S0166-4972(00)00040-7   DOI
30 K. H. Kim & J. Y. Jung. (2013). A Typology of Industry Convergences Based on Sources for Convergence Industries and Analysis of Critical Success Factors. Journal of the Korean Institute of Industrial Engineers, 39(3), 204-211. http://dx.doi.org/10.7232/JKIIE.2013.39.3.204   DOI
31 T. K. Ryu et al. (2012). Development of Indicators for IP Competitivenes and Characteristics. Seoul : Korea Institute of Intellectual Property.