Skip to main content
SpringerLink
Log in

Stochastic model for innovation and resulting skew distribution for technological concentration with verification in Japanese industry

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Technological resources are shown to be more concentrated to a few firms than economic wealth. To explain such concentrations, the self-multiplication process with cycle between the innovative and stagnant ages is modeled in terms of the stochastic process. This yields a family of new distributions which is named the ultra-Yule distribution. This new distribution which is quite skew is show to fit the real distributions of patents and of R & D expenditure in the Japanese industry better than the Yule distribution. The properties of this new distribution is discussed.

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

Similar content being viewed by others

References

  1. J. AITCHISON, J. A. C. BROWN,The Lognormal Distribution, Cambridge University Press, Cambridge, 1957.

    Google Scholar 

  2. F. M. BASS, A New Product Growth Model for Consumer Durables,Management Science. 15 (1969) No. 5, 215–227.

    Google Scholar 

  3. H. ETO, K. MAKINO, Theoretical and Empirical Analysis of Differentiation Process in Technology Gap between Developed and Developing Nations, in:International and Regional Conflicts: Quantitative Approaches, W. ISARD et. al. Eds, Chap. 9, 149–159, Ballinger Pub. C., Cambridge, Mass., 1983.

    Google Scholar 

  4. W. FELLER,An Introduction to Probability Theory and Its Applications, I, John Wiley, New York, 1950.

    Google Scholar 

  5. Y. IJIRI, H. A. SIMONSkew Distributions and the Sizes of Business Firms, North-Holland, Amsterdam, 1977.

    Google Scholar 

  6. Japan Patent Information Center, JAPATIC Data Base for Top 2000 Firms. Tokyo, 1981.

  7. G. L. LILIEN, The Implication of Diffusion Models for Accelerating the Diffusion of Innovation,Techonological Forecasting and Social Change, 17 (1980) 339–351.

    Google Scholar 

  8. V. MAHAJAN, R. A. PETERSON, Integrating Time and Space in Technological Substitution Models,Technological Forecasting and Social Change, 14 (1979) 231–241.

    Google Scholar 

  9. Nippon Keizai Shimbun (Nippon Economic Journal), Corporate Informations, 1980 Fall and 1981 Fall, Tokyo,

  10. D. SAHAL, A Theory of Measurmeent of Technological Change, InternationalJ. Systems Science, 8 (1977) No. 6, 671–682.

    Google Scholar 

  11. Science and Technology Agency of Prime Ministers Office of Japan (Ed), Science and Technology Indicator, 1981, Tokyo.

  12. A. L. YABLONSKY, On Fundamental Regularities of the Distribution of Scientific Productivity,Scientometrics 2 (1980) 3–34.

    Google Scholar 

  13. H. YODA,Introduction to Reliability Theory (in Japanese), Asakura Pub. C., Tokyo, 1972.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Socio-Technology, The University of Tsukuba, 305, Sakura, Ibaraki, (Japan)

    H. Eto

  2. Department of Mathematics, Chuo University, Kasuga, Bunkyo-ku, 112, Tokyo, (Japan)

    K. Makino

Authors
  1. H. Eto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Makino
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Eto, H., Makino, K. Stochastic model for innovation and resulting skew distribution for technological concentration with verification in Japanese industry. Scientometrics 5, 219–243 (1983). https://doi.org/10.1007/BF02019739

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02019739

Keywords

Search

Navigation