, 70:183 | Cite as

Patent analysis of genetic engineering research in Japan, Korea and Taiwan

  • Szu-chia Lo


The aim of this study is to reveal the research growth, the distribution of research productivity and impact of genetic engineering research in Japan, Korea and Taiwan by taking patent bibliometrics approach. This study uses quantitative methods adopt from bibliometrics to analyze the patents granted to Japan, Korea and Taiwan by United States Patent and Trademark Office (USPTO) from 1991 to 2002. In addition to patent and citation count, Bradford’s Law is applied to identify core assignees in genetic engineering. Patent coupling approach is taken to further analyze the patents granted to the core assignees to enclose the correlations among the core assignees.

13,055 genetic engineering patents were granted during the period of 1991 to 2002. Japan, Korea and Taiwan own 841 patents and Japan owns most of them. 270 assignees shared 841 patents and 16 core assignees are identified by the Bradford’s Law. 18,490 patents were cited by the 13,055 patents and 1,146 out of the 18,490 cited patents were granted to Japan, Korea and Taiwan. The results show Japan performs best in productivity and research impact among three countries. The core assignees are also Japan based institutions and four technical clusters are identified by patent coupling.


Citation Count Patent Citation Research Impact International Patent Classification Bibliographic Coupling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Albert, A., Plaza, L. M. (2004), The transfer of knowledge from the Spanish public R&D system to the productive sectors in the field of biotechnology. Scientometrics, 59(1): 3–14.CrossRefGoogle Scholar
  2. Allen, J. Oppenheim, C. (1979). The overlap of US and Canadian patents literature with journal literature. World Patent Information, 1(2): 77–80.CrossRefGoogle Scholar
  3. Banerjee, P., Gupta, B. M., Garg, K. C. (2000), Patent statistics as indicators of competition: an analysis of patenting in biotechnology. Scientometrics, 47(1): 95–116.CrossRefGoogle Scholar
  4. Bellardo, T. (1980), The use of co-citations to study science. Library Research, 2(3): 231–237.Google Scholar
  5. Cawkell, A. E. (1976), Understanding science by analyzing its literature. The Information Scientist, 10(1): 3–10.Google Scholar
  6. Demidowicz, B. K., Oppenheim, C. (1981), The overlap of patent and journal literature on animal feedstuffs. World Patent Information, 3: 82–83.Google Scholar
  7. Egghe, L., Rousseau, R. (1990), Introduction to Informetrics: Quantitative Methods in Library, Documentation and Information Science. Amsterdam, The Netherlands: Elsevier Science Publishers.Google Scholar
  8. Eisenschitz, T. S., Lazard, A. M., Willey, C. J. (1986), Patent groups and their relationship with journal literature. Journal of Information Science, 12: 53–58.Google Scholar
  9. Eisenschitz, T. S., McKie, L. J., Warne, K. (1989), Communication of information in U.S. biotechnology patents. World Patent Information, 11(1): 28–32.CrossRefGoogle Scholar
  10. Garfield, E. (1979), Citation Indexing: Its Theory and Application in Science, Technology and the Humanities. New York: Wiley.Google Scholar
  11. Garfield, E. (1980), Bradford’s law and related statistical patterns. Current Contents, 19: 5–12.Google Scholar
  12. Garfield, E. (1998), From citation indexes to informetrics: is the tail now wagging the dog? Libri, 48: 67–80.CrossRefGoogle Scholar
  13. Karki, M. M. S. (1997), Patent citation analysis: a policy analysis tool. World Patent Information, 33(4): 269–272.CrossRefMathSciNetGoogle Scholar
  14. Kessler, M. (1963), Bibliographic coupling between scientific papers. American Documentation, 14: 10–25.Google Scholar
  15. Lo, Szu-Chia (2004), A Study of the Productivity of Genetic Engineering Research from 1991 to 2002 Using the Patentometrics Approach. International Workshop on Webometrics, Informetrics and Scientometrics & Fifth COLLNET Meeting, Roorkee, India.Google Scholar
  16. Lopez-Munoz, F., Alamo, C., Rubio, G., Garcia-Garcia, P., Martin-Agueda, B., Cuenca, E. (2003), Bibliometric analysis of biomedical publications on SSRI during 1980–2000. Depression and Anxiety, 18(2): 95–103.CrossRefGoogle Scholar
  17. Moed, H. F. (2000), Bibliometric indicators reflect publication and management strategies. Scientometrics, 47(2): 323–346.CrossRefGoogle Scholar
  18. Narin, F. (1994), Patent bibliometrics. Scientometrics, 30(1): 147–155.CrossRefGoogle Scholar
  19. Narin, F. (1995), Patents as indicators for the evaluation of industrial research output. Scientometrics, 34(3): 489–496.CrossRefGoogle Scholar
  20. Narin, F., Moll, J. K. (1977), Bibliometrics. Annual Review of Information Science and Technology, 12: 35–58.Google Scholar
  21. Narin, F., Olivastro, D., Stevens, K. A. (1994), Bibliometric/theory practice and problems. Evaluation Review, 18(1): 65–76.Google Scholar
  22. Price, D. J. De Solla (1965), Networks of scientific papers. Science, 149(3683): 510–515.CrossRefGoogle Scholar
  23. Ramani, S. V., De Looze, M.-A. (2002), Using patent statistics as knowledge base indicators in the biotechnology sector: an application to France, Germany and the U.K. Scientometrics, 54(3): 319–346.CrossRefGoogle Scholar
  24. Small, H. (1973), Co-citation in the scientific literature: a new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(3): 265–269.Google Scholar
  25. Walker, R. D. (1995), Patents as Scientific and Technical Literature, Metuchen, N.J.: The Scarecrow Press.Google Scholar
  26. Weinberg, B. H. (1974), Bibliographic coupling: a review. Information Storage and Retrieval, 10(5/6): 189–196.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó 2007

Authors and Affiliations

  1. 1.University LibraryNational Cheng-Kung UniversityTainanTaiwan

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