Skip to main content
SpringerLink
Log in

Technology–industry networks in technology commercialization: evidence from Korean university patents

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Although there is increasing interest in policy issues on university patents, studies hitherto have focused on certain limited factors or case studies. By using a two-mode network analysis, this study identifies idiosyncratic patterns and differences in technology–industry networks between the two groups of Korean university patents—commercialized and non-commercialized. We collected patent data including bibliographic information from Korean universities that have run a patent management advisor dispatch program since 2005. Then, network analysis and analysis of variance for the two groups were conducted to investigate the group differences. We found that the structure of the technology–industry network was significantly more direct and simpler for commercialized than for non-commercialized patents. Specifically, we found that both direct and indirect linkages between technology and related industry were more complex for the non-commercialized group than for the commercialized one: the direct linkage was stronger for the commercialized than for the non-commercialized group. Our study suggests an important aspect of technology commercialization from the perspective of the inherent characteristics of patents, which is at variance with the evolutionary approaches of previous studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. The 23 universities were randomly selected by the Korean government. Therefore, selection bias was not significant in our data. The size and R&D investment of those universities were in keeping with the overall distribution among Korean universities.

  2. When we changed this criterion to around 3 years, the results were not significantly affected.

  3. Based on a comparative analysis of sleeping patents of universities, industry, and research institutes (KIIP 2011) and the Regulation on the Management of National Research and Development Projects of Korea, Article 17 Clause 5.

  4. C20: Manufacture of chemicals and chemical products except pharmaceuticals and medicinal chemicals.

  5. C25: Manufacture of fabricated metal products, except machinery and furniture.

  6. C26: Manufacture of electronic parts, computers, radio, television, and communication equipment and apparatus.

  7. C27: Manufacture of medical, precision and optical instruments, watches, and clocks.

  8. C29: Manufacture of other machinery and equipment.

  9. H01: Basic electrical goods.

  10. H04: Electronic communications .

  11. G03: Photography, cinematography, analogous techniques using waves other than optical waves, electrography, holography.

  12. H05: Electric techniques not otherwise provided for.

  13. C21: Manufacture of pharmaceuticals, medicinal chemicals, and botanical products.

  14. A61: Medical or veterinary science, hygiene.

  15. G01: Measuring, testing.

  16. Regulation on the Management of National Research Development Projects (Executive Order) Article 20 Clause 6.

References

  • Anderson, T. R., Daim, T. U., & Lavoie, F. F. (2007). Measuring the efficiency of university technology transfer. Technovation, 27, 306–318.

    Article  Google Scholar 

  • Archibugi, D., & Pianta, M. (1996). Measuring technological change through patents and innovation surveys. Technovation, 16(9), 451–468.

    Article  Google Scholar 

  • Baba, Y., Shichijo, N., & Sedita, S. R. (2009). How do collaborations with universities affect firms’ innovative performance? The role of “Pasteur scientists” in the advanced materials fields. Research Policy, 38, 756–764.

    Article  Google Scholar 

  • Baldini, N. (2008). Negative effects of university patenting: Myths and grounded evidence. Scientometrics, 75(2), 289–311.

    Article  Google Scholar 

  • Ballester, C., Calvo-Armengol, A., & Zenou, Y. (2006). Who’s who in networks. Wanted: The key player. Econometrica, 74(5), 1403–1417.

    Article  MATH  MathSciNet  Google Scholar 

  • Basole, R.C. (2009). Structural analysis and visualization of ecosystems: A study of mobile device platforms. Proceedings of the 15th Americas Conference on Information Systems (pp. 1–10).

  • Basole, R. C. (2009b). Visualization of interfirm relations in a converging mobile ecosystem. Journal of Information Technology, 24, 144–159.

    Article  Google Scholar 

  • Borgatti, S. P. (2006). Identifying sets of key players in a social network. Computational and Mathematical Organization Theory, 12, 21–34.

    Article  MATH  Google Scholar 

  • Braun, T., Dióspatonyi, I., Zádor, E., & Zsindely, S. (2007). Journal gatekeepers indicator-based top universities of the world, of Europe and of 29 countries: A pilot study. Scientometrics, 71(2), 155–178.

    Article  Google Scholar 

  • Calvert, J., & Patel, P. (2002). University–industry research collaborations in the UK. Science and Public Policy, 30(2), 85–96.

    Article  Google Scholar 

  • Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston: Harvard Business School Press.

    Google Scholar 

  • Cho, T. S., & Shih, H. Y. (2011). Patent citation network analysis of core and emerging technologies in Taiwan: 1997–2008. Scientometrics, 89(3), 795–811.

    Article  Google Scholar 

  • Choi, C., Shin, J., Yoon, B., Lee, W., & Park, Y. (2004). On the linkage between industries and technologies: patent citation analysis. Proceedings of IEEE International Engineering Management Conference (pp. 576–580).

  • Conceicao, P., Heitor, M. V., & Oliveira, P. (1998). University-based technology licensing in the knowledge based economy. Technovation, 18(10), 615–625.

    Article  Google Scholar 

  • Czarnitzki, D. & Bento, C. L. (2011). Innovation subsidies: Does the funding source matter for innovation intensity and performance? Empirical evidence from Germany. ZEW (Center for European Economic Research), Discussion Paper, 11-053, 1–46.

  • Czarnitzki, D., Hussinger, K., & Schneider, C. (2009). Why challenge the ivory tower? New evidence on the basicness of academic patents. Kyklos, 62(4), 488.

    Article  Google Scholar 

  • Dorsey, E. R., Roulet, J., Thompson, J. P., Reminick, J. I., Thai, A., White, Z., et al. (2010). Funding of US biomedical research, 2003–2008. The Journal of the American Medical Association, 303(2), 137–143.

    Article  Google Scholar 

  • Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25, 233–242.

    Article  Google Scholar 

  • Etzkowitz, H. (2008a). The entrepreneurial university. In H. Etzkowitz (Ed.), The triple helix (pp. 27–42). New York: Routledge.

    Chapter  Google Scholar 

  • Etzkowitz, H. (2008b). The incubation of innovation. In H. Etzkowitz (Ed.), The triple helix (pp. 105–121). New York: Routledge.

    Chapter  Google Scholar 

  • Etzkowitz, H., & Leydesdorff, L. (1997). Universities in the global knowledge economy: A triple helix of academic–industry–government relation. London: Cassell Academy.

    Google Scholar 

  • Fabrizio, K. R., & Minin, A. D. (2008). Commercializing the laboratory: Faculty patenting and the open science environment. Research Policy, 37, 914–931.

    Article  Google Scholar 

  • Foray, D., & Lissoni, F. (2010). University research and public–private interaction. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovation (Vol. 1, pp. 276–308). UK: Elsevier.

    Google Scholar 

  • Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1, 215–239.

    Article  Google Scholar 

  • Freitas, I. M. B., Marques, R. A., & Paula e Silva, E. M. (2012). University–industry collaboration and innovation in emergent and mature industries in new industrialized countries. Research Policy, 41 (in press).

  • Gay, B., & Dousset, B. (2005). Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry. Research Policy, 34(10), 1457–1475.

    Article  Google Scholar 

  • Gibbons, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary societies. London: SAGE Publications.

    Google Scholar 

  • Gilbert, R. J., & Newbery, D. M. G. (1982). Preemptive patenting and the persistence of monopoly. The American Economics Review, 72(3), 514–526.

    Google Scholar 

  • Giuliani, E., & Arza, V. (2009). What drives the formation of ‘valuable’ university–industry linkages? Insights from the wine industry. Research Policy, 38, 906–921.

    Article  Google Scholar 

  • Guellec, D., & Pottelsberghe, B. V. (2004). From R&D to productivity growth: Do the institutional settings and the source of funding of R&D matter? Oxford Bulletin of Economics and Statistics, 66(3), 353–378.

    Article  Google Scholar 

  • Henderson, R., Jaffe, A. D., & Trajtenberg, M. (1998). Universities as a source of commercial technology: A detailed analysis of university patenting, 1965–1988. The Review of Economics and Statistics, 80(1), 119–127.

    Article  Google Scholar 

  • Hicks, D. & Hamilton, K. (1999). Does university–industry collaboration adversely affect university research?. Resource document. Issues in Science and Technology Online. http://www.nap.edu/issues/15.4/realnumbers.htm.

  • Johnson, D. (2002). The OECD technology concordance (OTC): Patents by industry of manufacture and sector of use (DSTI/DOC Vol. 5). Paris: OECD.

    Book  Google Scholar 

  • Kamada, T., & Kawai, S. (1989). An algorithm for drawing general undirected graphs. Information Processing Letters, 31, 7–15.

    Article  MATH  MathSciNet  Google Scholar 

  • Keller, R., Eckert, C. M., & Clarkson, P. J. (2006). Metrics or node-link diagrams: Which visual representation is better for visualizing connectivity models? Information Visualization, 5(1), 62–76.

    Article  Google Scholar 

  • KIIP (Korea Institute of Intellectual Property). (2011). A promotion model of utilization of sleeping patents in the perspective of industry and technology market. Seoul: KIIP.

    Google Scholar 

  • Kim, B., Hong, J., & Kim, M. (2008). The study on the composition of linkage framework between IPC and KSIC. Daejeon: Korean Intellectual Property Office (KIPO).

    Google Scholar 

  • KIPO. (2011). Report on the analysis of patent performances in national R&D program and directions for policy. Daejeon: KIPO.

    Google Scholar 

  • Kortum, S., & Putnam, J. (1997). Assigning patents to industries: Tests of the Yale technology concordance. Economic System Research, 9(2), 161–175.

    Article  Google Scholar 

  • Lee, H., Kim, C., Cho, H., & Park, Y. (2009a). An ANP-based technology network for identification of core technologies: A case of telecommunication technologies. Technovation, 36, 894–908.

    Google Scholar 

  • Lee, W., Park, Y., Yoon, B., & Shin, J. (2004). Analysis of technology–industry linkage and Korean firms’ patent strategy utilizing information from patent database. Seoul: Science & Technology Policy Institute (STEPI).

    Google Scholar 

  • Lee, D. H., Seo, I. W., Choe, H. C., & Kim, H. D. (2012). Collaboration network patterns and research performance: the case of Korean public research institutions. Scientometrics, 91, 925–942.

    Article  Google Scholar 

  • Lee, S., Yoon, B., & Park, Y. (2009b). An approach to discovering new technology opportunities: Keyword-based patent map approach. Technovation, 29, 481–497.

    Article  Google Scholar 

  • Lerner, J., & Merges, R. P. (1997). Patent scope and emerging industries. In D. B. Yoffie (Ed.), Competing in the age of digital convergence (pp. 301–324). Boston: Harvard Business School Press.

    Google Scholar 

  • Meyer, M., Siniläinen, T., & Utecht, J. T. (2003). Towards hybrid triple helix indicators: A study of university-related patents and a survey of academic inventors. Scientometrics, 58(2), 321–350.

    Article  Google Scholar 

  • Mowery, D. C., & Sampat, B. N. (2005). Universities in national innovation systems. In J. Fagerberg, D. C. Mowery, & R. R. Nelson (Eds.), The oxford handbook of innovation (pp. 209–239). New York: Oxford University Press.

    Google Scholar 

  • No, H. J., & Park, Y. (2010). Trajectory patterns of technology fusion: Trend analysis and taxonomical grouping in nanobiotechnology. Technological Forecasting and Social Change, 77, 63–75.

    Article  Google Scholar 

  • Nohria, N., & Garcia-Pont, C. (1991). Global strategic linkages and industry structure. Strategic Management Journal, 12(1), 105–124.

    Article  Google Scholar 

  • Nooy, W. D., Mrvar, A., & Batagelj, V. (2005). Exploratory social network analysis with Pajek. New York: Cambridge University Press.

    Book  Google Scholar 

  • Park, H. W., & Leydesdorff, L. (2010). Longitudinal trends in networks of university–indsutry–government relations in South Korea: The role of programmatic incentives. Research Policy, 39, 640–649.

    Article  Google Scholar 

  • Park, Y., Yoon, B., & Lee, S. (2005). The idiosyncrasy and dynamism of technological innovation across industries: Patent citation analysis. Technology in Society, 27, 471–485.

    Article  Google Scholar 

  • Phelps, C. C. (2010). A longitudinal study of the influence of alliance network structure and composition on firm exploratory innovation. Academy of Management Journal, 53(4), 890–913.

    Article  Google Scholar 

  • Pitkethly, R. H. (2001). Intellectual property strategy in Japanese and UK companies: Patent licensing decisions and learning opportunities. Research Policy, 30, 425–442.

    Article  Google Scholar 

  • Powers, J. (2004). R&D funding sources and university technology transfer: What is stimulating universities to be more entrepreneurial? Research in Higher Education, 45(1), 1–23.

    Article  Google Scholar 

  • Powers, J. B., & McDougall, P. P. (2005). University start-up formation and technology licensing with firms that go public: A resource-based view of academic entrepreneurship. Journal of Business Venturing, 20, 291–311.

    Article  Google Scholar 

  • Rasmussen, E. (2008). Government instruments to support the commercialization of university research: Lessons from Canada. Technovation, 28, 506–517.

    Article  Google Scholar 

  • Rasmussen, E., Moen, O., & Gulbrandsen, M. (2006). Initiatives to promote commercialization of university knowledge. Technovation, 26, 518–533.

    Article  Google Scholar 

  • Rogers, J. D., Bozeman, B., & Chompalov, I. (2001). Obstacles and opportunities in the application of network analysis to the evaluation of R&D. Research Evaluation, 10(3), 161–172.

    Article  Google Scholar 

  • Sanyal, P. (2003). Understanding patents: The role of R&D funding sources and the patent office. Economics of Innovation and New Technology, 12(6), 507–529.

    Article  Google Scholar 

  • Scott, J. (2003). Social network analysis: A handbook. London: SAGE Publications.

    Google Scholar 

  • Shin, J., & Park, Y. (2010). Evolutionary optimization of a technological knowledge network. Technovation, 30, 612–626.

    Article  Google Scholar 

  • Siegel, D. S., Veugelers, R., & Wright, M. (2007). Technology transfer offices and commercialization of university intellectual property: Performance and policy implications. Oxford Review of Economic Policy, 23(4), 640–660.

    Article  Google Scholar 

  • Thursby, J. G., Fuller, A. W., & Thursby, M. (2009). US faculty patenting: Inside and outside the university. Research Policy, 38, 14–25.

    Article  Google Scholar 

  • von Hippel, E. (1988). Democratizing innovation. Cambridge: MIT Press.

    Google Scholar 

  • Wang, X., Liu, D., Ding, K., & Wang, X. (2012). Science funding and resource output: A study on 10 countries. Scientometrics, 91, 591–599.

    Article  Google Scholar 

  • Wang, X., Xu, S., Wang, Z., Peng, L., & Wang, C. (2013). International scientific collaboration of China: Collaborating countries, institutions and individuals. Scientometrics, 95, 885–894.

    Article  Google Scholar 

  • Wasserman, S., & Faust, K. (2006). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Google Scholar 

  • Wong, P. K., & Singh, A. (2010). University patenting activities and their link to the quantity and quality of scientific publications. Scientometrics, 83, 271–294.

    Article  Google Scholar 

  • Wong, P. K., & Singh, A. (2013). Do co-publications with industry lead to higher levels of university technology commercialization activity? Scientometrics (in press).

Download references

Acknowledgments

This work was supported by National Research Foundation (NRF) of Korea funded by Korean Government (Ministry of Education, Science and Technology: NRF-2012-S1A3A-2033860, NRF-2011-013-B00051, NRF-22B20130012672) and by Korea Institute of Intellectual Property (KIIP). The premise of this study was based on data provided by Korean Intellectual Property Office (KIPO) under the sponsored project of “The Academic Research Support Program for Analysis of IP (intellectual property).” Also, data analysis process was collaboratively conducted with the Korea Institute of Patent Information (KIPI).

Author information

Authors and Affiliations

  1. Graduate School of Innovation and Technology Management, KAIST, 335 Gwahangno, Yuseong-gu, Daejeon, 305-701, Republic of Korea

    Yongrae Cho & Wonjoon Kim

Authors
  1. Yongrae Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wonjoon Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wonjoon Kim.

Appendix

Appendix

See Table 5.

Table 5 IPC Section and four-digit KSIC code with the highest matching probability (The construction of this table was supported by KIPI)
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cho, Y., Kim, W. Technology–industry networks in technology commercialization: evidence from Korean university patents. Scientometrics 98, 1785–1810 (2014). https://doi.org/10.1007/s11192-013-1131-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-013-1131-4

Keywords

Mathematical Subject Classification (2010)

JEL Classification

Search

Navigation