Skip to main content
Log in

Principal parameters affecting R&D exploitation of nanotechnology research: a case for Korea

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

The purpose of this study is to determine principal parameters which affect the R&D exploitation and to explore R&D activities in closed science that positively affect those in open science. Based on 486 nanotechnology projects from five national R&D programs in South Korea, canonical correlation analysis is used to analyze the relationships among R&D parameters of inputs, outputs and outcomes and to determine principle parameters. As a result, this study concludes that the principal parameters are publications with high impact, patents, and academic degrees. This study also shows a positive correlation between activities in open science and closed science. The conclusions suggest that research results with high impact value should be endorsed by the Korean government and should try to keep a balance between R&D exploitation in open science and closed science. This study would be used for establishing South Korea’s R&D policy effective for faster commercialization of nanotechnology related research.

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

Access this article

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. Public R&D is defined as R&D performed within the public sector which is universities, public research institutes, research hospitals and the like (Bentzen and Smith 2001).

  2. Triple helix is a spiral model of innovation by the collaboration of academia, government, and industry which creates new knowledge, technology, or products and services that are transmitted to intended final users in fulfillment of a social need (Gibbons et al. 1994; Etzkowitz and Leydesdorff 1997).

References

  • Arundel, A., & Bordoy, C. (2006). The 2006 ASTP Survey. Association of European Science and Technology Transfer Professionals, Den Hague: ASTP. Accessed 23 November 2012. http://www.astp.net/Survey/Final%20ASTP%20report%20June%2014%202006.pdf.

  • Arundel, A., & Bordoy, C. (2008). Developing internationally comparable indicators for the commercialization of publicly-funded research. UNU-MERIT Working Paper 2008-075. Accessed November 23 2012, http://www.merit.unu.edu/publications/papers/200610_arundel_bordoy.pdf.

  • Bentzen, J., & Smith, V. (2001). Spillovers in R&D activities: An empirical analysis of the Nordic countries. International Advances in Economic Research, 7(2), 199–212.

    Article  Google Scholar 

  • Bouros, D. (2007). Measurement of individual scientific work. Pneumon, 1(20), 19–21.

    Google Scholar 

  • Brown, M. G., & Svenson, R. A. (1998). Measuring R&D productivity. Research Technology Management, 31(4), 30–35.

    Google Scholar 

  • Carlsson, B., & Fridh, A. (2002). Technology transfer in United States universities: A survey and statistical analysis. Journal of Evolutionary Economics, 12, 199–232.

    Article  Google Scholar 

  • Chubin, D. E. (1985). Open science and closed science: Tradeoffs in a democracy. Science, Technology and Human Values, 10(2), 73–81.

    Article  Google Scholar 

  • Coccia, M. (2008). Measuring scientific performance of public research units for strategic change. Journal of Informetrics, 2, 183–194.

    Article  Google Scholar 

  • Cohen, W. M., Nelson, R. R., & Walsh, J. P. (2002). Links and Impacts: The influence of public research on industrial R&D. Management Science, 38(1), 1–23.

    Article  Google Scholar 

  • European Commission. (2002). An Assessment of the Implications for Basic Genetic Engineering Research of Failure to Publish, or Late Publication of, Papers on Subjects which could be Patentable as required under Article 16(b) of Directive 98/44/EC on the Legal Protection of Biotechnological Inventions. Brussels: EC.

  • Debackere, K., & Veugelers, R. (2005). The role of academic technology transfer organizations in improving industry science links. Research Policy, 34(3), 321–342.

    Article  Google Scholar 

  • Di Gregorio, D., & Shane, S. (2003). Why do some universities generate more start-ups than others? Research Policy, 32, 209–227.

    Article  Google Scholar 

  • Etzkowitz, H., & Leydesdorff, L. (1997). Universities and the Global Knowledge Economy: A Triple Helix of University-Industry-Government Relations. London: Pinter.

    Google Scholar 

  • European Commission. (2009). Nanosciences and Nanotechnologies: An action plan for Europe 2005–2009. Second Implementation Report 2007–2009. Brussels: EC. Accessed November 23 2012, http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2009:0607:FIN:EN:PDF.

  • 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 

  • Feng, Y. J., Lu, H., & Bi, K. (2004). An AHP/DEA method for measurement of the efficiency of R&D management activities in universities. International Transactions in Operational Research, 11, 181–191.

    Article  Google Scholar 

  • Friedman, J., & Silberman, J. (2003). University technology transfer: Do incentives, management, and location matter? Journal of Technology Transfer, 28(1), 81–85.

    Article  Google Scholar 

  • Garfield, E., & Welljams-Dorof, A. (1992). Of Nobel class: A citation perspective on high impact research authors. Theoretical Medicine, 13, 117–135.

    Article  Google Scholar 

  • Garg, K. C., Gupta, B. M., Jamal, T., Roy, S., & Kumar, S. (2005). Assessment of impact of AICTE funding on R&D and educational development. Scientometrics, 65(2), 151–160.

    Article  Google Scholar 

  • Geuna, A., & Nesta, L. J. J. (2006). University patenting and its effects on academic research: The emerging European evidence. Research Policy, 35(6), 790–807.

    Article  Google Scholar 

  • Gibbons, M., Limoges, C., Nowotny, H., Schwartzmann, S., Scott, P., & Trow, M. (1994). The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies. London: Sage.

    Google Scholar 

  • Giuri, P., Mariani, M., Brusoni, S., Crespi, G., Francoz, D., Gambardella, A., et al. (2007). Inventors and invention processes in Europe: Results from the PatVal-EU survey. Research Policy, 36, 1107–1127.

    Article  Google Scholar 

  • Guan, J. C., & Wang, G. B. (2010). A comparative study of research performance in nanotechnology for China’s inventor–authors and their non-inventing peers. Scientometrics, 84, 331–343.

    Article  Google Scholar 

  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). New Jersey: Pearson Education.

    Google Scholar 

  • Harhoff, D., & Reitzig, M. (2004). Determinants of opposition against EPO patent grants—the case of biotechnology and pharmaceuticals. International Journal of Industrial Organization, 22, 443–480.

    Article  Google Scholar 

  • Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.

    Article  Google Scholar 

  • House Committee on Science. (1998). Unlocking Our Future: Toward a New National Science Policy. Washington: HCS. Accessed November 23 2012, http://www.gpo.gov/fdsys/pkg/GPO-CPRT-105hprt105-b/pdf/GPO-CPRT-105hprt105-b.pdf.

  • Hullmann, A. (2007). Measuring and assessing the development of nanotechnology. Scientometrics, 70(3), 739–758.

    Article  Google Scholar 

  • Hullmann, A., & Meyer, M. (2003). Publications and patents in nanotechnology. Scientometrics, 58(3), 507–527.

    Article  Google Scholar 

  • Hung, W. C., Lee, L. C., & Tsai, M. H. (2009). An international comparison of relative contributions to academic productivity. Scientometrics, 81(3), 703–718.

    Article  Google Scholar 

  • Islam, N., & Miyazaki, K. (2010). An empirical analysis of nanotechnology research domains. Technovation, 30, 229–237.

    Article  Google Scholar 

  • Jennings, C. (1998). Citation data: The wrong impact? Nature Neuroscience, 1(8), 641–642.

    Article  Google Scholar 

  • Jensen, R., & Thursby, M. (2001). Proofs and prototypes for sale: The licensing of university inventions. American Economic Review, 91(1), 240–259.

    Article  Google Scholar 

  • Jung, U. K., & Seo, D. W. (2010). An ANP approach for R&D project evaluation based on interdependencies between research objectives and evaluation criteria. Decision Support Systems, 49, 335–342.

    Article  Google Scholar 

  • Kay, L., & Shapira, P. (2009). Developing nanotechnology in Latin America. Journal of Nanoparticle Research, 11(2), 259–278.

    Article  Google Scholar 

  • King, D. A. (2004). The scientific impact of nations. Nature, 430, 311–316.

    Article  Google Scholar 

  • Kocher, M. G., Luptacik, M., & Sutter, M. (2006). Measuring productivity of research in economics: A cross-country study using DEA. Socio-Economic Planning Sciences, 40(4), 314–332.

    Article  Google Scholar 

  • Korhonen, P., Tainio, R., & Wallenius, J. (2001). Value efficiency analysis of academic research. European Journal of Operational Research, 130, 121–132.

    Article  MATH  Google Scholar 

  • Kuah, C. T., & Wong, K. Y. (2011). Efficiency assessment of universities through data envelopment analysis. Procedia Computer Science, 3, 499–506.

    Article  Google Scholar 

  • Lach, S., & Schankerman, M. (2003). Royalty sharing and technology licensing in universities. Journal of the European Economic Association, 2(2–3), 252–264.

    Google Scholar 

  • Lanjouw, J. O., & Schankerman, M. (2004). Patent quality and research productivity: measuring innovation with multiple indicators. Economic Journal, 114, 441–465.

    Article  Google Scholar 

  • Lee, H. Y., & Park, Y. Y. (2005). An international comparison of R&D efficiency: DEA approach. Asian Journal of Technology Innovation, 13(2), 207–221.

    Article  Google Scholar 

  • Lee, H. Y., Park, Y. T., & Choi, H. G. (2009). Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach. European Journal of Operational Research, 196, 847–855.

    Article  MATH  Google Scholar 

  • Li, X., Lin, Y., Chen, H., & Roco, M. C. (2007). Worldwide nanotechnology development: a comparative study of USPTO, EPO, and JPO patents (1976–2004). Journal of Nanoparticle Research, 9, 977–1002.

    Article  Google Scholar 

  • Link, A. N., & Siegel, D. S. (2005). Generating science-based growth: An econometric analysis of the impact of organizational incentives on university-industry technology transfer. European Journal of Finance, 11(3), 169–182.

    Article  Google Scholar 

  • Liu, J. S., & Lu, W. M. (2010). DEA and ranking with the network-based approach: a case of R&D performance. Omega, 38, 453–464.

    Article  Google Scholar 

  • Lockett, A., & Wright, M. (2005). Resources, capabilities, risk capital and the creation of university spin-out companies. Research Policy, 34(7), 1043–1057.

    Article  Google Scholar 

  • Lux Research. (2007). International Activity Drivers Nanotechnology Forward. New York: Lux Research.

    Google Scholar 

  • Marinova, D., & McAleer, M. (2003). Nanotechnology strength indicators: international rankings based on US patents. Nanotechnology, 14, R1–R7.

    Article  Google Scholar 

  • Markman, G., Phan, P., Balkin, D., & Gianiodis, P. (2004). Entrepreneurship from the ivory tower: Do incentive systems matter? Journal of Technology Transfer, 29(3–4), 353–364.

    Article  Google Scholar 

  • Meyer, M. (2006). Are patenting scientists the better scholars? An exploratory comparison of inventor–authors with their non-inventing peers in nano-science and technology. Research Policy, 35(10), 1646–1662.

    Article  Google Scholar 

  • Meyer, M., Debackere, K., & Glanzel, W. (2010). Can applied science be ‘good science’? Exploring the relationship between patent citations and citation impact in nanoscience. Scientometrics, 85, 527–539.

    Article  Google Scholar 

  • Ministry of Education, Culture, Sports, Science and Technology. (2011). The 4th Science and Technology Basic Plan. Tokyo: MEXT. Accessed November 23 2012, http://www.mext.go.jp/component/a_menu/science/detail/__icsFiles/afieldfile/2011/08/19/1293746_02.pdf.

  • Miyazaki, K., & Islam, N. (2007). Nanotechnology systems of innovations—An analysis of industry and academia research activities. Technovation, 27, 661–675.

    Article  Google Scholar 

  • Moed, H. F. (2005). Citation Analysis in Research Evaluation. Dordrecht: Springer.

    Google Scholar 

  • Moed, H. F. (2009). New developments in the use of citation analysis in research evaluation. Archivum Immunologiae et Therapiae Experimentalis, 57, 13–18.

    Article  Google Scholar 

  • Moed, H. F., Debruin, R. E., & Van leeuwen, T. N. (1995). New bibliometric tools for the assessment of National research performance—database description, overview of indicators and first applications. Scientometrics, 33(3), 381–422.

    Article  Google Scholar 

  • Mowery, D. C., & Sampat, B. N. (2004). The Bayh–Dole Act and university–industry technology transfer: a model for other OECD governments? Journal of Technology Transfer, 30(1), 115–127.

    Article  Google Scholar 

  • Murray, F. (2004). The role of academic inventors in entrepreneurial firms: sharing the laboratory life. Research Policy, 33, 643–659.

    Article  Google Scholar 

  • Nanoscale Science, Engineering and Technology Subcommittee. (2011). National Nanotechnology Initiative strategic plan. Washington: National Science and Technology Council. Accessed November 23 2012. http://www.nano.gov/sites/default/files/pub_resource/2011_strategic_plan.pdf.

  • National Research Foundation of Korea. (2011). 2010 White Paper on University-Industry Cooperation in Korea. Daejeon: NRF. Accessed November 23 2012, Available on http://www.nrf.re.kr.

  • National Science Board. (2012). Science and Engineering Indicators 2012. Arlington: NSB. Accessed November 23 2012, http://www.nsf.gov/statistics/seind12/start.htm.

  • National Science and Technology Commission. (2005). The 2nd Korea National Nanotechnology Development Plan (2006–2015). Seoul: NSTC. Accessed November 23 2012, Available on http://www.nstc.go.kr.

  • National Science and Technology Commission. (2011). The 3rd Korea National Nanotechnology Development Plan (2011–2020). Seoul: NSTC. Accessed 23 November 2012, Available on http://www.nstc.go.kr.

  • Nelson, A. J. (2009). Measuring knowledge spillovers: What patents, licenses and publications reveal about innovation diffusion. Research Policy, 38, 944–1005.

    Article  Google Scholar 

  • O’Shea, R., Allen, T., & Chevalier, A. (2005). Entrepreneurial orientation, technology transfer, and spin-off performance of U.S. universities. Research Policy, 34(7), 994–1009.

    Article  Google Scholar 

  • Perkmann, M., & West, J. (2012). Open science and open innovation: sourcing knowledge from universities. Handbook of University Technology Transfer, University of Chicago Press, Forthcoming. Accessed January 30 2013, http://ssrn.com/abstract=2133397.

  • Powell, W. W., Owen-Smith, J., & Colyvas, J. A. (2007). Innovation and emulation: lessons from American universities in selling private rights to public knowledge. Minerva, 45, 121–142.

    Article  Google Scholar 

  • Powers, J. B., & McDougall, P. (2005). Policy orientation effects on performance with licensing to start-ups and small companies. Research Policy, 34(7), 1028–1042.

    Article  Google Scholar 

  • Pudovkin, A.I., & Garfield, E., (2004). Rank-normalized impact factor: A way to compare journal performance across subject categories. Proceedings of the 67th ASIS&T Annual Meeting, vol. 41, pp. 507–515.

  • Ramirez, A. M., Garcia, E. O., & Rio, A. D. (2000). Renormalized impact factor. Scientometrics, 47, 3–9.

    Article  Google Scholar 

  • Rinia, E. J., Van Leeuwen, Th N, Van Vuren, H. G., & Van Raan, A. F. J. (1998). Comparative analysis of a set of bibliometrics indicators and central peer review criteria. Evaluation of condensed matter physics in the Netherlands. Research Policy, 27, 95–107.

    Article  Google Scholar 

  • Roco, M. C. (2011). The long view of nanotechnology development: the national nanotechnology initiative at 10 years. Journal of Nanoparticle Research, 13, 427–445.

    Article  Google Scholar 

  • Sampat, B. (2006). Patenting and US academic research in the twentieth century: the world before and after Bayh Dole. Research Policy, 35(6), 772–789.

    Article  Google Scholar 

  • Seglen, P. O. (1997). Why the impact factor of journals should not be used for evaluating research. British Medical Journal, 314, 498–502.

    Article  Google Scholar 

  • Sherry, A., & Henson, R. K. (2005). Conducting and interpreting canonical correlation analysis in personality research: A user-friendly primer. Journal of Personality Assessment, 84(1), 37–48.

    Article  Google Scholar 

  • Siegel, D. S., Waldman, D. A., Atwater, L. E., & Link, A. N. (2004). Toward a model of the effective transfer of scientific knowledge from academicians to practitioners: qualitative evidence from the commercialization of university technologies. Journal of Engineering and Technology Management, 21, 114–142.

    Article  Google Scholar 

  • Soltani, A. M., Tabatabaeian, S. H., Hanafizadeh, P., & Soofi, J. B. (2011). An evaluation scheme for nanotechnology policies. Journal of Nanoparticle Research, 13, 7303–7312.

    Article  Google Scholar 

  • Sombatsompop, N., & Markpin, T. (2005). Making an equality of ISI impact factors for different subject fields. Journal of the American Society for Information Science and Technology, 56(7), 676–683.

    Article  Google Scholar 

  • State Council. (2006). National medium- to long-range program for scientific and technological development (2006–2020). Beijing: State Council. Accessed November 23 2012, http://www.gov.cn/jrzg/2006-02/09/content_183787.htm.

  • Thompson, B. (1991). A primer on the logic and use of canonical correlation analysis. Measurement and Evaluation in Counseling and Development, 24, 80–95.

    Google Scholar 

  • Thursby, J. G., & Kemp, S. (2002). Growth and productive efficiency of university intellectual property licensing. Research Policy, 31(1), 109–124.

    Article  Google Scholar 

  • Tijssen, R. J. W., Visser, M. S., & Van Leeuwen, T. N. (2002). Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference? Scientometrics, 54(3), 381–397.

    Article  Google Scholar 

  • Wang, E. C., & Huang, W. (2007). Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach. Research Policy, 36(2), 260–273.

    Article  Google Scholar 

  • Youtie, J., Shapira, P., & Porter, A. L. (2008). Nanotechnology publications and citations by leading countries and blocs. Journal of Nanoparticle Research, 10, 981–986.

    Article  Google Scholar 

  • Yu, G., Wang, M. Y., & Yu, D. R. (2010). Characterizing knowledge diffusion of Nanoscience & Nanotechnology by citation analysis. Scientometrics, 84, 81–97.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hoo-Gon Choi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cho, YD., Choi, HG. Principal parameters affecting R&D exploitation of nanotechnology research: a case for Korea. Scientometrics 96, 881–899 (2013). https://doi.org/10.1007/s11192-013-0974-z

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-013-0974-z

Keywords

Navigation