DOI QR코드

DOI QR Code

A Study on the Determinants of Patent Citation Relationships among Companies : MR-QAP Analysis

기업 간 특허인용 관계 결정요인에 관한 연구 : MR-QAP분석

  • Park, Jun Hyung (Graduate School of Business IT, Kookmin University) ;
  • Kwahk, Kee-Young (School of Management Information Systems, Kookmin University) ;
  • Han, Heejun (NTIS Project Management Team, NTIS Center, Korea Institute of Science and Technology Information) ;
  • Kim, Yunjeong (NTIS Project Management Team, NTIS Center, Korea Institute of Science and Technology Information)
  • 박준형 (국민대학교 비즈니스IT전문대학원) ;
  • 곽기영 (국민대학교 경영대학 경영정보학부) ;
  • 한희준 (KISTI NTIS센터, NTIS사업팀) ;
  • 김윤정 (KISTI NTIS센터, NTIS사업팀)
  • Received : 2013.09.02
  • Accepted : 2012.10.05
  • Published : 2013.12.31

Abstract

Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

최근 지식기반 사회의 진입과 더불어 지식재산에 대한 관심이 증가하고 있다. 특히 하이테크산업을 이끌고 있는 ICT기업들은 지식재산의 체계적 관리를 위하여 끊임없이 노력하고 있다. 기업의 지적 자본을 대표하는 특허정보가 지속적으로 축적됨에 따라 정량적인 분석이 가능해졌다. 특허정보를 통하여 특허수준부터 기업수준, 산업수준, 국가수준에 이르기 까지 다양한 수준에서의 분석이 가능하다. 특허정보는 기술 현황을 파악하거나 성과에 미치는 영향을 분석하는데 활용되고 있다. 네트워크를 통한 분석은 지식 영향의 흐름을 나타내며, 이를 통하여 기술의 변화를 확인할 수 있을 뿐만 아니라 앞으로의 연구 방향을 예측할 수 있다. 네트워크를 활용한 분석 분야에서는 기업이 차지하는 네트워크상에서의 위치가 기업성과에 미치는 영향을 다각도에서 분석하는 연구가 진행되고 있다. 특허 인용 정보를 활용한 분석은 크게 두 가지로, 인용 횟수를 활용하는 인용지표 분석과 인용관계를 바탕으로 한 네트워크 분석으로 나뉜다. 본 연구는 기업간 규모의 차이가 기업 간 특허 인용 관계에 미치는 영향을 분석하고자 하였다. S&P 500에 등록된 IT 및 통신서비스를 제공하는 74개 기업을 선정하였으며 기업 간 특허 인용 관계를 구하기 위하여 2009년, 2010년의 특허 인용 정보를 수집하여 기업 간 특허 인용 관계를 나타냈다. 또한 기업규모를 대표하는 지표로 기업 총 자산에 대한 정보를 수집하였다. 기업규모에 따라 외부 지식에 대한 의존도가 달라지는 선행연구를 통하여 기업규모가 기업간 특허 인용 관계에 미치는 영향을 알아보고자 하였다. 이에 기업 간 총 자산의 차이에 절대값을 취한 값을 기업 간 거리로 정의하였으며, 기업 간 규모의 단순 차이를 기업 간 계층으로 정의하여 새로운 소시오매트릭스를 생성하였다. 2010년도 기업간 특허 인용 관계를 나타낸 소시오매트릭스를 종속변수로 하였으며, 2009년도 기업 간 특허 인용 네트워크, 기업 간 거리 및 계층을 독립변수로 하여 QAP분석 및 MR-QAP분석을 실시하였다. QAP분석 결과 기업 간 거리와 계층은 특허 인용 관계에 유의한 영향을 미치는 것으로 나타났다. MR-QAP분석에는 2009년도 기업 간 특허 인용 관계와 기업 간 거리만 유의함을 확인할 수 있었다. 특히 2009년도 기업 간 특허 인용 관계가 2010년도 기업 간 특허 인용 관계에 가장 큰 영향력을 행사하는 것을 볼 수 있어 기업 간 특허 인용관계는 연속성이 존재하는 것으로 볼 수 있었다.

Keywords

References

  1. Albert, M. B., D. Avery, F. Narin and P. McAllister, "Direct Validation of Citation Counts as Indicator of Industrially Import Patents," Journal Research Policy, Vol.20, No.3(1991), 251-259. https://doi.org/10.1016/0048-7333(91)90055-U
  2. Audretsch, D. B. and M. Vivarelli, "Small Firms and R&D Spillovers: Evidence from Italy," Revue d'Economie Industrielle, Vol.67, No.1 (1994), 225-237. https://doi.org/10.3406/rei.1994.1520
  3. Cantner, U. and H. Graf, "The network of innovators in Jena: An application of social network analysis," Research Policy, Vol.35, No.4(2006), 463-480. https://doi.org/10.1016/j.respol.2006.01.002
  4. Carpenter, M. P., N. Francis and W. Patricia, "Citation Rates to Technologically Important Patents," World Patent Information, Vol.3, No.4(1981), 160-163. https://doi.org/10.1016/0172-2190(81)90098-3
  5. Chang, Sh. B., K. K. Lai and Sh. M. Chang, "Exploring Technology Diffusion and Classification of Business Methods: Using the Patent Citation Network," Technological Forecasting and Social Change, Vol.76, No.1 (2009), 107-117. https://doi.org/10.1016/j.techfore.2008.03.014
  6. Choi, J. H. and N. I. Kim, "Keyword Network Analysis for Technology Forecasting," Journal of Intelligence and Information Systems, Vol.17, No.4 (2011), 227-240.
  7. Dempwolf, C. S. and W. Lyles. "The Uses of Social Network Analysis in Planning: A Review of The Literature," Journal of Planning Literature, Vol.27, No.1(2012), 3-21. https://doi.org/10.1177/0885412211411092
  8. Ernst, H., "Patent Information for Strategic Technology Management," World Patent Information, Vol.25, No.3(2003), 233-242. https://doi.org/10.1016/S0172-2190(03)00077-2
  9. Fung, M. K. and W. W. Chow, "Measuring the Intensity of Knowledge Flow with Patent Statistics," Economic Letters, Vol.74, No.3 (2001), 353-358.
  10. Hall, B., A. Jaffe and M. Trajtenberg, The NBER Patent Citations Data File : Lessons, Insights and Methodological Tools, Cambridge, MA, 2001.
  11. Jaffe, A. B., M. Trajtenberg and M.S. Fogarty, "Knowledge Spillovers and Patent Citation: Evidence from a Survey of Inventors," American Economic Review, Vol.90, No.2(2000), 215-218. https://doi.org/10.1257/aer.90.2.215
  12. Jeon, K. E., Intellectual Property 21, KIPO, 1999. Available at http://www.kipo.go.kr/home/portal/nHtml/Data/NewKnowH.html#top (Accessed 13 June, 2013).
  13. Jung, M. A., Y. H. Choi and E. N. Heo, "Relationship between Innovative Capacities and IPR Performances among Korean Bio-firms," The Korean Economic Review, Vol. 55, No.4 (2007), 243-273.
  14. Kang, E. Y. and K.-Y. Kwahk, "Managing Duplicate Memberships of Websites : An Approach of Social Network Analysis," Journal of Intelligence and Information Systems, Vol.17, No.1(2011), 153-169.
  15. Karki, M. M. S., "Patent Citation Analysis : a Policy Analysis Tool," World Patent Information, Vol.19, No.4(1997), 269-272. https://doi.org/10.1016/S0172-2190(97)00033-1
  16. Kho, J., K. Cho and Y. Cho, "A Study on Recent Research Trend in Management of Technology Using Keywords Network Analysis," Journal of Intelligence and Information Systems, Vol.19, No.2(2013), 101-123. https://doi.org/10.13088/jiis.2013.19.2.101
  17. Kim, Y. S. and Y. J. Ko, "A Study on the Diffusion System of R&D Performance for Strengthening global Competitiveness Through Patent Analysis," The Journal of Intellectual Property, Vol.6, No.2(2011), 191-229.
  18. Kim, H. J. and K.-Y. Kwahk, "Effects of Centrality on IT Usage Capability : A Perspective of Social Networks," The Journal of Information Systems, Vol.20, No.1(2011), 147-169 https://doi.org/10.5859/KAIS.2011.20.1.147
  19. Kim, W. J., Y. R. Cho and N. I. Nam, Network Patterns of Patent-Centric Technological Knowledge and Innovation Strategy for a Mobile Industry, Korea Institute of Intellectual Property, 2012.
  20. Kutznets, S., Inventive Activity : Problems of Definition and Measurement, Universities-National Bureau, UMI, 1962.
  21. Kwahk, K.-Y., Social Network Analysis, Cheongram Publication, 2013(Forthcoming).
  22. Lanjouw, J. O., A. Pakes and J. Putnam, "How to Count Patents and Value Intellectual Property : the Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Vol.46, No.4(1998), 405-432. https://doi.org/10.1111/1467-6451.00081
  23. Lee, B., "The Exploratory Study on the Determinants of Innovation at the Firm Level : Social Network Analysis on Inventor's Network in Pharmaceutical Industry," The Journal of Intellectual Property, Vol.4, No.1(2009), 81-107. https://doi.org/10.1093/jiplp/jpn233
  24. Lee, K. H. and B. S., Yoon, "The Effects of Patents on Firm Value : Venture vs. non-Venture," Asian Journal of Technology Innovation, Vol. 14, No.1(2006), 67-99. https://doi.org/10.1080/19761597.2006.9668619
  25. Mogee and M. Ellen, "Using Patent Data for Technology Analysis and Planning," Research-Technology Management, Vol.34, No.4 (1991), 43-49.
  26. Nam, Y. J. and E. S. Jeong, "A Study on the Development of New Patent Index Used the Citation Information," Journal of Intelligence and Information Systems, Vol.23, No.1(2006), 221-241,
  27. Narin, F., E. Noma and R. Perry, "Patents as Indicators of Corporate, Technological Strength," Research Policy, Vol.16, No.2(1987), 143-155. https://doi.org/10.1016/0048-7333(87)90028-X
  28. Narin, F., K. S. Hamition and D. Oilvastro, "The Increasing Linkage between US Technology and Public Science," Research Policy, Vol.26, No.3(1997), 317-330. https://doi.org/10.1016/S0048-7333(97)00013-9
  29. OECD, The Measurement of Scientific and Technological Activities : Using as Science and Technology Indicators-Patent Manual, OECD Publishing, Paris, 1994.
  30. Park, K. H., "Analysis on the Characteristics of Knowledge Flows in Korea Using U.S. Patent," The Journal of Intellectual Property, Vol.1, No.2(2006), 66-93.
  31. Peter, N., R. Frietsch, T. Schubert and K. Blind, Patents and the Financial Performance of Firms-An Analysis based on Stock Market Data, Fraunhofer ISI, 2011.
  32. Seidel, A. H., "Citation system for patent office," Journal of the Patent Office Society, Vol.31 (1949), 554.
  33. Seo, J., O. J. Kwon, K. R. Noh, W. J. Kim and E. S. Jeong, "A Study on the Research Outcome Measurement and Application Using the Patent Citation Information," Proceedings of the Korea Technology Innovation Society Conference, 2006.
  34. Sung, T. K., "Determinants of Firm's Innovative Output: The Role of External Networks and Firm Size," Daehan journal of business, Vol. 18, No.4(2005), 1767-1788.
  35. Trajtenberg, M., "A Penny for Your Quotes: Patent Citations and the Value of Innovations," RAND Journal of Economics, Vol.21, No.1(1990), 172-187. https://doi.org/10.2307/2555502
  36. USTPOa, Chapter 2000 Duty of Disclosure, USTPO, May 2, 2004, Download at http://www.uspto. gov/web/offices/pac/mpep/mpep-2000.pdf (Downloaded 13 June, 2013).
  37. USTPOb, 706 Rejection of Claims, USTPO, Available at http://www.uspto.gov/web/offices/pac/mpep/s706. html (Accessed 13 June, 2013).
  38. Van Duijn, M. and Huisman, M., Statistical Models for Ties and Actors, Scott, J. and Carringto, P. J., SAGE publications, Inc., California, 2011.
  39. Wartburg, I. V., T. Teichert and K. Rost, "Inventive Progress Measured by Multi-stage Patent Citation Analysis," Research Policy, Vol.34, No.10(2005), 1591-1607. https://doi.org/10.1016/j.respol.2005.08.001
  40. Yang, Y. and H. Hwang, "Evolutionary and Validity Analysis of Korean New Venture Promotion Policy by Utilizing Social Network Theory," Korea Association of Applied Economics, Vol.7, No.1(2005), 187-214.
  41. Yang, Z. K., Q. N. Lie and Z. Y. Liu, "Top Ten Highly Cited Patents in USPTO," Proceedings of WIS 2008.
  42. Yoo, J. B. and Y. M. Chung, "A Study on Developing a Prediction Model of Patent Citation Counts," Korea Society for Information Management, Vol. 27, No.4(2010), 239-258. https://doi.org/10.3743/KOSIM.2010.27.4.239
  43. Yoon, B., R. Wook and Y. T. Park, "The Analysis of Inter-Industrial Knowledge Flow Structure among Northeast Asian Countries Based on Patent Citation Data : Comparison of Korea, Japan, and Taiwan," Asian journal of technology innovation, Vol.13, No.3(2005), 197-224.
  44. Yoon, B. G. and Y. T. Park, "A Text-Mining-Based Patent Network:Analytical Tool for High-Technology Trend," Journal of High Technology Management Research, Vol.15, No.1(2004), 37-50. https://doi.org/10.1016/j.hitech.2003.09.003
  45. Zvi, G., "Patent Statistics as Economic Indicators : A Survey," Journal of Economic Literature, Vol.28 (1990), 1661-1707.

Cited by

  1. An Application of Patent Citation Network Analysis for Technology Marketing: A Case of a Public Research Institute vol.16, pp.5, 2015, https://doi.org/10.5762/KAIS.2015.16.5.3210
  2. 특허 인용에 영향을 미치는 요인 분석: 국내의료기기 특허를 중심으로 vol.33, pp.2, 2013, https://doi.org/10.3743/kosim.2016.33.2.103
  3. ICT R&D and Technology Knowledge Flows in Korea : vol.29, pp.4, 2018, https://doi.org/10.4018/jdm.2018100103
  4. 기업 패널 DB를 활용한 대구지역 중소기업 기술혁신 결정요인 분석 vol.23, pp.1, 2013, https://doi.org/10.12812/ksms.2021.23.1.081