Receiving information at Korean and Taiwanese universities, industry, and GRIs


This article examines the incentive structure underlying information transfers received by the three key players of the Triple Helix paradigm: universities, industry, and government research institutes (GRIs). For Korea and Taiwan, which are the cases under analysis here, such an empirical examination has not yet been conducted on a quantitative level. Using a unique dataset of survey responses from a maximum of 325 researchers based in Korean and Taiwanese universities, industry, and GRIs, this article shows that there are some significant differences between and within countries. Most importantly, policy interventions to promote university-industry-GRI interactions impact the degree to which specific information transfers are considered useful. In Korea, formal transfers are emphasized, while both formal and, in particular, informal transfers are emphasized in Taiwan.

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  1. 1.

    This was proposed originally by Dasgupta and Maskin (1987).

  2. 2.

    SEMATECH targeted the increased competitiveness of US chip manufacturers, and the hands-off approach of the government enables SEMATECH participants to effectively manage the R&D consortia. PNGV was designed to improve national competitiveness in manufacturing through innovations which would achieve three times the fuel efficiency of 1994 family sedans (Roos et al. 1998).

  3. 3.

    Now the Lean Aerospace Initiative.

  4. 4.

    Evans (1998) actually outlines three models. The entrepreneurial function of the second model embodies the investment concerns of the third model, we believe.

  5. 5.

    For example, unlike the Korean case, Taiwan’s economic plans in the past have no implementation procedures, are not supported by controls, and lack credibility (Hamilton and Biggart 1988). As well, others subscribe to the view that Korea is “interventionist” while Taiwan is “supportive” (Park 1990). Specifically, there is evidence in Korea of domestic market protection and industrial targeting; in Taiwan, medium-term economic plans limit policymakers authority to allocate credit (Park 1990).

  6. 6.

    See Shapiro (2007) for historical accounts.

  7. 7.

    The ATP, incidentally, is the basis for several of the research funding programs in Korea and Taiwan from which the unique dataset of this paper is drawn.

  8. 8.

    Knowledge spillovers occur through reverse engineering or through the reading of other’s findings in published form, and full compensation is not awarded to the original source of such information. Market spillovers benefit the customer when the same price is paid for products of higher quality, which are the result of product innovations. As well, process innovations can lead to decreased production costs which result in lower prices, again benefiting the consumer. Network spillovers are exemplified by the successful coordination between research entities to create a new technology.

  9. 9.

    These studies, again, are minimized to the uni-directional transfer of information from the university to the firm.

  10. 10.

    This dataset was collected in the winter and spring of 2005–2006, following field research and interviews by the author with public and private research directors in Korea (summer 2005) and Taiwan (winter 2005).

  11. 11.

    Another source of funding are the increasingly popular university-based and GRI-based incubation centers. Despite their phenomena-like status, these SMEs and start-ups were not targeted in the survey for fear that they were not necessarily engaging in cross-sector R&D collaboration or lacked sufficient expertise.

  12. 12.

    Cited from

  13. 13.

    Cheng et al. (1998) list the following coordinating mechanisms: U.S. aid, the strong central bank, and a number of organizing structures and bodies peripheral but connected to the government.

  14. 14.

    The questionnaire was distributed and collected by the author, ministry-level officials, GRI-based directors, and government agency officials.

  15. 15.

    This is, again, tied to limits of the available information.

  16. 16.

    When firms are large enough, they will often possess the infrastructure and capabilities to engage in basic R&D, but these large enterprises are not considered samples in the dataset, and there will be no discussion of their impact and influence.

  17. 17.

    The rectangular boxes in each figure represent those responses between the twenty-fifth percentile (lower hinge) and the seventy-fifth percentile (upper hinge). The median is found directly in the middle of the box. Lines (or “whiskers”) extending from the box are capped with adjacent values, beyond which are outside values, represented by small circles. Adjacent values are calculated by multiplying the interquartile range (the difference between the first and third quartile values) by 1.5, and adding or subtracting it from the upper or lower hinges, respectively.

  18. 18.

    A Taiwan (i.e., country) dummy was used. Additional details about right-hand side variables in this preliminary test of country differences include the following: sector dummies were included, and a three-level categorical variable was included to test for differences across universities, industry, and GRIs.

  19. 19.

    The model on which these measures are based includes UIG, country, and research sector dummies. Coefficients and/or marginal effects for these are not included in Tables 4 and 5.

  20. 20.

    The model on which these measures are based includes UIG, country, and research sector dummies. Coefficients and/or marginal effects for these are not included in Table 6.


  1. Adams, J. D., Chiang, E. P., & Starkey, K. (2001). Industry–university cooperative research centers. Journal of Technology Transfer, 26(1–2), 73–86.

    Article  Google Scholar 

  2. Aldrich, J. H., & Nelson, F. D. (1984). Linear probability, logit, and probit models. Newbury Park: Sage Publications.

    Google Scholar 

  3. Amemiya, T. (1985). Advanced econometrics. Cambridge: Harvard University Press.

    Google Scholar 

  4. Amsden, A. (1989). Asia’s next giant: South Korea and late industrialization. New York: Oxford University Press.

    Google Scholar 

  5. Berger, S., & Lester, K. R. (Eds.). (2005). Global Taiwan: Building competitive strengths in the new economy. New York: M.E. Sharpe.

    Google Scholar 

  6. Bernstein, J. I., & Nadiri, M. I. (1988). Interindustry R&D spillovers, rates of return, and production in high-tech industries. American Economic Review, 78(2), 429–434.

    Google Scholar 

  7. Branscomb, L. M., & Keller, J. H. (1998). Towards a research and innovation policy. In L. M. Branscomb & J. H. Keller (Eds.), Investing in innovation: Creating a research and innovation policy that works. Cambridge: MIT Press.

    Google Scholar 

  8. Branstetter, L., & Sakakibara, M. (1997). Japanese research consortia: A microeconometric analysis of industrial policy. NBER Working Paper No. 6066. NBER, Cambridge.

  9. Breschi, S., & Catalini, C. (2010). Tracing the links between science and technology: An exploratory analysis of scientists’ and inventors’ networks. Research Policy, 39(1), 14–26. doi:10.1016/j.respol.2009.11.004.

  10. Breznitz, D. (2005). Development, flexibility, and R&D performance in the Taiwanese IT industry—capability creation and the effects of state-industry co-evolution. Industrial and Corporate Change, 14(1), 153–187.

    Article  Google Scholar 

  11. Cassiman, B., Veugelers, R., & Zuniga, P. (2008). In search of performance effects of (in)direct industry science links. Industrial and Corporate Change, 17(4), 611–646. doi:10.1093/icc/dtn023.

    Google Scholar 

  12. Cheng, T.-J., Haggard, S., & Kang, D. (1998). Institutions and growth in Korea and Taiwan: The bureaucracy. Journal of Development Studies, 34(6), 87–111.

    Article  Google Scholar 

  13. Cohen, W. M., Florida, R., Randazzese, L., & Walsh, J. (1998). Industry and the academy: Uneasy partners in the cause of technological advance. In R. G. Noll (Ed.), Challenges to research universities. Washington, D.C.: The Brookings Institution.

    Google Scholar 

  14. Cohen, W. M., Nelson, R. R., & Walsh, J. P. (2002). Links and impacts: The influence of public research on industrial R&D. Management Science, 48(1), 1–23.

    Google Scholar 

  15. Dasgupta, P., & Maskin, E. (1987). The simple economics of research portfolios. The Economic Journal, 97, 581–595.

    Article  Google Scholar 

  16. D’Aspremont, C., & Jacquemin, A. (1988). Cooperative and noncooperative R&D in duopoly with spillovers. American Economic Review, 78(5), 1133–1137.

    Google Scholar 

  17. David, P. A., & Foray, D. (1996). Information distribution and the growth of economically valuable knowledge: A rationale for technological infrastructure policies. In M. Teubal, D. Foray, M. Justman, & E. Zuscovitch (Eds.), Technological infrastructure policy: An international perspective (pp. 87–116). New York: Kluwer Academic Publishers.

    Google Scholar 

  18. David, P. A., Hall, B. H., & Toole, A. A. (2000). Is public R&D a complement or substitute for private R&D? A review of the econometric evidence. Research Policy, 29(4–5), 497–529.

    Article  Google Scholar 

  19. Etzkowitz, H. (2003). Innovation in innovation: The triple helix of university–industry–government relations. Social Science Information, 42(3), 293–337.

    Article  Google Scholar 

  20. Etzkowitz, H. (2008). Triple helix innovation: Industry, university, and government in action. London: Routledge.

    Google Scholar 

  21. Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From national systems and “Mode 2” to a triple helix of university–industry–government relations. Research Policy, 29(2), 109–123.

    Article  Google Scholar 

  22. Evans, P. B. (1998). Transferable lessons? Re-examining the institutional prerequisites of East Asian economic policies. Journal of Development Studies, 34(6), 66–86.

    Article  Google Scholar 

  23. Fontana, R., Guena, A., & Mireille, M. (2003). Firm size and openness: The driving forces of university–industry collaboration. A report commissioned by the OST-DTI, SPRU, University of Sussex, Brighton.

  24. Fritsch, M. & Schwirten, C. (1999). Enterprise-university co-operation and the role of public research institutions in regional innovation systems. Industry and Innovation, 6(1), 69–83.

    Google Scholar 

  25. Griliches, Z. (1998). The search for R&D spillovers. In R&D and productivity: The econometric evidence. Chicago: University of Chicago Press.

  26. Hagedoorn, J., Link, A., & Vonortas, N. S. (2000). Research partnerships. Research Policy, 29, 567–586.

    Article  Google Scholar 

  27. Hall, B. H., Link, A. N., & Scott, J. T. (2000). Universities as Research Partners, NBER Working Paper No. 7643. NBER, Cambridge.

  28. Hamilton, G. G., & Biggart, N. W. (1988). Market, culture, and authority: A comparative analysis of management and organization in the far east. American Journal of Sociology, 94(Supplement), S52–S94.

    Article  Google Scholar 

  29. Han, Y. (2001). What drives R&D alliances? Evidence from the biotechnology industry. Ph.D. Dissertation. Los Angeles: University of Southern California.

  30. Hsueh, L.-M., Hsu, C.-k., & Perkins, D. H. (Eds.). (2001). Industrialization and the state: The changing role of government in Taiwan’s economy, 1945–1998. Cambridge: Harvard Institute for International Development.

    Google Scholar 

  31. Hu, M.-C. (2011). Evolution of knowledge creation and diffusion: The revisit of Taiwan’s Hsinchu science park. Scientometrics, 88(3), 949–977.

    Google Scholar 

  32. Hu, M.-C., & Mathews, J. A. (2009). Estimating the innovation effects of university-industry-government linkages: The case of Taiwan. Journal of Management and Organization, 15(2), 138–154.

    Article  Google Scholar 

  33. Jaffe, A. B. (1998). The importance of ‘Spillovers’ in the policy mission of the advanced technology program. Journal of Technology Transfer, 23(2), 11–19.

    Article  Google Scholar 

  34. Johnson, C. (1982). MITI and the Japanese miracle: The growth of industrial policy, 1925–1975. Stanford: Stanford University Press.

    Google Scholar 

  35. Joly, P. B., & Mangamatin, V. (1996). Profile of public laboratories, industrial partnerships and organisation of R&D: The dynamics of industrial relationships in a large research organisation. Research Policy, 25(6), 901–922.

    Article  Google Scholar 

  36. Kim, H., & Park, Y. (2008). The impact of R&D collaboration on innovative performance in Korea: A Bayesian network approach. Scientometrics, 75(3), 535–554. doi:10.1007/s11192-007-1857-y.

    Article  Google Scholar 

  37. Lécuyer, C. (1998). Academic science and technology in the service of industry: MIT creates a “Permeable” engineering school. AEA Papers and Proceedings: Clio and the Economic Organization of Science, 88(2), 28–33.

    Google Scholar 

  38. Lee, W.-Y. (2000). the role of science and technology policy in Korea’s industrial development. In L. Kim & R. R. Nelson (Eds.), Technology learning and innovation: Experiences of newly industrializing economies. Cambridge: Cambridge University Press.

    Google Scholar 

  39. Leydesdorff, L. (2006). The knowledge-based economy and the triple helix model. In W. Dolfsma & L. Soete (Eds.), Understanding the dynamics of a knowledge economy. Cheltenham: Edward Elgar.

    Google Scholar 

  40. Manjarres-Henriquez, L., Gutierrez-Gracia, A., & Vega-Jurado, J. (2008). Coexistence of university–industry relations and academic research: Barrier to or incentive for scientific productivity. Scientometrics, 76(3), 561–576.

    Article  Google Scholar 

  41. McKelvey, R. D., & Zavoina, W. (1975). A statistical model for the analysis of ordinal level dependent variables. Journal of Mathematical Sociology, 4(1), 103–120.

    Article  MATH  MathSciNet  Google Scholar 

  42. Mowery, D. C., Nelson, R. R., Sampat, B. N., & Ziedonis, A. A. (2004). Ivory tower and industrial innovation: Univeristy–industry technology transfer before and after the Bayh-Dole act in the United States. Stanford: Stanford Business Books.

    Google Scholar 

  43. Nelson, R. R., & Rosenberg, N. (1993). Technical innovation and national systems. In R. R. Nelson (Ed.), National innovation systems: A comparative analysis. New York: Oxford University Press.

    Google Scholar 

  44. OECD. (2004). OECD science, technology and industry outlook 2004. Paris and Washington, D.C.: OECD.

    Google Scholar 

  45. OECD. (2006). Main science and technology indicators (MSTI). Accessed on 24 July 2006.

  46. Park, Y. C. (1990). Development lessons from Asia: The role of government in South Korea and Taiwan. American Economic Review, 80(2), 118–121.

    Google Scholar 

  47. Park, H. W., Hong, H. D., & Leydesdorff, L. (2005). A comparison of the knowledge-based innovation systems in the economies of South Korea and the Netherlands using triple helix indicators. Scientometrics, 65(1), 3–27.

    Article  Google Scholar 

  48. Rahm, D., Kirkland, J., & Bozeman, B. (1999). University–industry R&D collaboration in the United States, the United Kingdom, and Japan. New York: Kluwer Academic Publishers.

    Google Scholar 

  49. Rinia, E., van Leeuwen, T., Bruins, E., van Vuren, H., & van Raan, A. (2002). Measuring knowledge transfer between fields of science. Scientometrics, 54(3), 347–362. doi:10.1023/A:1016078331752.

    Article  Google Scholar 

  50. Roos, D., Field, F., & Neely, J. (1998). Industry consortia. In L. M. Branscomb & J. H. Keller (Eds.), Investing in innovation: Creating a research and innovation policy that works. Cambridge: MIT Press.

    Google Scholar 

  51. Ruegg, R., & Feller, I. (2003). A toolkit for evaluating public R&D investment: Models, methods, and findings from ATP’s first decade. Washington, D.C.: National Institute of Standards and Technology & U.S. Department of Commerce.

    Google Scholar 

  52. Sakakibara, M. (1994). Cooperative research and development: Theory and evidence on Japanese practice. Doctoral Dissertation. Harvard: Harvard University.

  53. Scott, A., Steyn, G., Guena, A., Brusoni, S., & Steinmueller, E. (2001). The economic returns to basic research and the benefits of university–industry relationships: A literature review and update of findings. A report commissioned by the OST-DTI, SPRU, University of Sussex, Brighton.

  54. Shapiro, M. A. (2007). The triple helix paradigm in Korea: A test for new forms of capital. International Journal of Technology Management and Sustainable Development, 6(3), 171–191.

    Article  Google Scholar 

  55. Stiglitz, J. E., & Jayadev, A. (2010). Medicine for tomorrow: Some alternative proposals to promote socially beneficial research and development in pharmaceuticals. Journal of Generic Medicines 7(3), 217–226.

    Article  Google Scholar 

  56. Stiglitz, J. E., & Wallsten, S. J. (1999). Public-private technology partnerships: Promises and pitfalls. American Behavioral Scientist, 43(1), 52–73.

    Article  Google Scholar 

  57. Wade, R. (1990). Governing the market: Economic theory and the role of government in East Asian industrialization. Princeton: Princeton University Press.

    Google Scholar 

  58. World Bank. (1993). The East Asian miracle: Economic growth and public policy. New York: World Bank, Oxford University Press.

    Google Scholar 

  59. Zhang, L., Glänzel, W., & Liang, L. (2009). Tracing the role of individual journals in a cross-citation network based on different indicators. Scientometrics, 81(3), 821–838. doi:10.1007/s11192-008-2245-y.

    Article  Google Scholar 

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The author wishes to thank Jeffrey Nugent, Jang-Jae Lee, Jung-Jae Lee, and Chintay Shih. Special thanks go out to Ki-Sik Park and Sang Sub Cho of ETRI’s IT Strategy Research Group and Hubert Chen and Jian Hung Chen of ITRI’s Industrial Economics and Knowledge Center.

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Correspondence to Matthew A. Shapiro.



Information transfers construct:

[On questionnaires for respondents at GRIs and universities] To what extent does useful information move from private firms to your institute?

[On questionnaires for respondents at private firms] To what extent does useful information move from public institutes to your firm?

Please answer for the following methods.

(1 = no movement at all; 7 = a lot of movement)

Patents 1 2 3 4 5 6 7
Publications 1 2 3 4 5 6 7
Meetings or conferences 1 2 3 4 5 6 7
Hires 1 2 3 4 5 6 7
Contract research 1 2 3 4 5 6 7
Consulting 1 2 3 4 5 6 7

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Shapiro, M.A. Receiving information at Korean and Taiwanese universities, industry, and GRIs. Scientometrics 90, 289–309 (2012).

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  • R&D collaboration
  • Information flows
  • Triple helix relations
  • Information transfer
  • East Asian developmental state
  • Technology spillovers

MSL Classification

  • 91F99
  • 62P20
  • 62P25
  • 62J05
  • 62J10

JEL Classification

  • O31
  • O32
  • O33
  • O34
  • O39