, Volume 51, Issue 1, pp 9–36 | Cite as

Application of statistical physics methods and conceptsto the study of science & technology systems

  • Luis A. N. Amaral
  • P. Gopikrishnan
  • Kaushik Matia
  • Vasiliki Plerou
  • H. E. Stanley


We apply methods and concepts of statistical physics to the study of science & technology(S&T) systems. Specifically, our research is motivated by two concepts of fundamentalimportance in modern statistical physics: scaling and universality. We try to identify robust,universal, characteristics of the evolution of S&T systems that can provide guidance to forecastingthe impact of changes in funding. We quantify the production of research in a novel fashioninspired by our previous study of the growth dynamics of business firms. We study the productionof research from the point of view both of inputs (R&D funding) and of outputs (publications andpatents) and find the existence of scaling laws describing the growth of these quantities.We also analyze R&D systems of different countries to test the "universality" of our results.We hypothesize that the proposed methods may be particularly useful for fields of S&T (or forlevels of aggregation) for which either not enough information is available, or for which evolutionis so fast that there is not enough time to collect enough data to make an informed decision.


Statistical Physic Technology System Informed Decision Physic Method Growth Dynamic 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    National Science Board, Science & Engineering Indicators-2000, National Science Foundation, Arlington VA, 2000.Google Scholar
  2. 2.
    E. Mansfield, Academic research and industrial-innovation, Research Policy, 20 (1991) 1-12.Google Scholar
  3. 3.
    A. Pakes, K. L. Sokoloff, Science, technology, and economic growth, Proc. Nat. Ac. Sci. USA, 93 (1996) 12655-12657.Google Scholar
  4. 4.
    H. Grupp, The links between competitiveness, firms' innovative activities and public R&D support in Germany: An empirical analysis, Technol. Anal. Strateg., 9 (1997) 19-33.Google Scholar
  5. 5.
    Program of Sixth International Conference on Science and Technology Indicators (S&T 2000), CWTS, Leiden, 2000.Google Scholar
  6. 6.
    E. Garfield, Citation Indexing: Its Theory and Applications in Science, Technology and Humanities, Wiley, New York, 1979.F. NARIN, Evaluative Bibliometrics. The Use of Publication and Citation Data in the Evaluation of scientific activity, National Science Foundation, Washington DC, 1976. A. SCHUBERT, W. GLÄNZEL, T. BRAUN, Scientometric datafiles: A comprehensive set of indicators on 2649 journals and 96 countries in all major science fields and subfields 1981-1985, Scientometrics, 16 (1989) 3-478. M. B. ALBERT, D. AVERY, F. NARIN, P. MCALLISTER, Direct validation of citation counts as indicators of industrially important patents, Research Policy, 20 (1991) 251-259. H. GRUPP, The measurement of technical performance of innovations by technometrics and its impact on established technology indicators, Research Policy, 23 (1994) 175-193. P. O. SEGLEN, Citation rates and journal impact factors are not suitable for evaluation of research, Acta. Orthop. Scand., 69 (1998) 224-229. Scientometrics 51 (2001) S. TEITEL, Scientific publications, research-and-development expenditures, country size, and per-capita income: A cross-section analysis, Technol. Forecast. Soc., 46 (1994) 175-187. A. F. J. VAN RAAN, Advanced bibliometric methods as quantitative core of peer review based evaluation and foresight exercises, Scientometrics, 36 (1996) 397-420. F. NARIN, D. OLIVASTRO, Linkage between patents and papers: An interim EPO/US comparison, Scientometrics, 41 (1998) 51-59. A. F. J. VAN RAAN, Scientometrics: State-of-the-art, Scientometrics, 38 (1997) 205-218. E. C. M. NOYONS, M. LUWEL, H. F. MOED, Combining mapping and citation analysis for evaluative bibliometric purposes, J. Am. Soc. Inf. Sci., 50 (1999) 115-131.Google Scholar
  7. 7.
    K. Buchholz, Criteria for the analysis of scientific quality, Scientometrics, 32 (1995) 195-218. A. T. BALABAN, How should citations to articles in high-and low-impact journals be evaluated, or what is a citation worth? Scientometrics, 37 (1996) 495-498. H. F. MOED, T. N. VAN LEEUWEN, J. REEDIJK, A critical analysis of the journal impact factors of Angewandte Chemie and the Journal of the American Chemical Society-Inaccuracies in published impact factors based on overall citations only, Scientometrics, 37 (1996) 105-116. P. VINKLER, Model for quantitative selection of relative scientometric impact indicators, Scientometrics, 36 (1996) 223-236. W. GLÄNZEL, The need for standards in bibliometric research and technology, Scientometrics, 35 (1996) 167-176. M. DE MARCHI, M. ROCCHI, Summing up approaches to the study of science and technology indicators, Scientometrics, 46 (1999) 39-49.Google Scholar
  8. 8.
    H. F. Moed, R. E. De Bruin, Th. N. Van Leeuwen, New bibliometric tools for the assessment of national research performance: Database description, overview of indicators and first applications, Scientometrics, 33 (1995) 381-422.Google Scholar
  9. 9.
    R. J. W. Tijssen, Th. N. Van Leeuwen, B. Verspagen, H. Hollanders, 1998 Science and Technology Indicators: Summary, A joint publication for the Dutch Ministry of Education, Culture and Science, Zoetermeer, 1998.Google Scholar
  10. 10.
    M. Luwel, E. C. M. Noyons, H. F. Moed, Bibliometric assessment of research performance in Flanders: Policy background and implications, R&D Management, 29 (1999) 133-141.Google Scholar
  11. 11.
    H. F. Moed, Th. N. Van Leeuwen, M. S. Visser, Trends in publication output and impact of universities in the Netherlands, in: Proceedings of the 5th International Conference on Science and Technology Indicators, edited by H. F. MOED, Hinxton, Cambridge UK, 1998, Research Evaluation, 8 (1999) 60-67.Google Scholar
  12. 12.
    M. Luwel, A bibliometric profile of Flemish research in natural, life and technical sciences, Scientometrics, 47 (2000) 281-302.Google Scholar
  13. 13.
    V. Plerou, L. A. N. Amaral, P. Gopikrishnan, M. Meyer, H. E. Stanley, Similarities between the growth dynamics of university research and of competitive economic activities, Nature, 400 (1999) 433-437.Google Scholar
  14. 14.
    H. F. Moed, M. Luwel, Science policy: the business of research, Nature, 400 (1999) 411-412.Google Scholar
  15. 15.
    R. Jackiw, Introducing scale symmetry, Phys. Today, 25(1) (1972) 23-27.Google Scholar
  16. 16.
    P. J. E. Peebles, The Large-Scale Structure of the Universe, Princeton University Press, Princeton, 1980.Google Scholar
  17. 17.
    R. N. Mantegna, H. E. Stanley, Scaling behavior in the dynamics of an economic index, Nature, 376 (1995) 46-49. R. N. MANTEGNA, H. E. STANLEY, Turbulence and exchange markets, Nature, 383 (1996) 587-588.Google Scholar
  18. 18.
    H. E. Stanley, Introduction to Phase Transitions and Critical Phenomena, Oxford, Oxford University Press, 1971.Google Scholar
  19. 19.
    H. E. Stanley, Scaling, universality, and renormalization: Three pillars of modern critical phenomena, Rev. Mod. Phys., 71 (1999) S358-S366 [Special Issue for the Centennial of the American Physical Society].Google Scholar
  20. 20.
    C.-K. Peng, S. V. Buldyrev, A. L. Goldberger, S. Havlin, F. Sciortino, M. Simons, H. E. Stanley, Long-range correlations in nucleotide sequences, Nature, 356 (1992) 168-171. A. ARNEODO, E. BACRY, P. V. GRAVES, J. F. MUGY, Characterizing long-range correlations in DNAsequences from wavelet analysis, Phys. Rev. Lett., 74 (1995) 3293-3296.Google Scholar
  21. 21.
    B. Suki, A.-L. BarabÁsi, Z. Hantos, F. PetÁk, H. E. Stanley, Avalanches and power law behaviour in lung inflation, Nature, 368 (1994) 615-618.Google Scholar
  22. 22.
    B. T. Hyman et al., quantitative analysis of senile plaques in Alzheimer disease: Observation of lognormal size distribution and of differences associated with apolipoprotein e genotype and trisomy 21 (Down Syndrome), Proc. Natl. Acad. Sci. USA, 92 (1995) 3586-3590. L. CRUZ et al., Aggregation and disaggregation of senile plaques in alzheimer disease, Proc. Natl. Acad. Sci. USA, 94 (1997) 7612-7616. R. B. KNOWLES et al., Plaque-induced neural network disruption in Alzheimer's disease, Proc. Natl. Acad. Sci. USA, 96 (1999) 5274-5279.Google Scholar
  23. 23.
    C.-K. Peng, S. Havlin, H. E. Stanley, A. L. Goldberger, Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series, Chaos, 5 (1995) 82-87. L. A. N. AMARAL, A. L. GOLDBERGER, P. Ch. IVANOV, H. E. STANLEY, Scale-independent measures and pathologic cardiac dynamics, Phys. Rev. Lett., 81 (1998) 2388-2391. P. Ch. IVANOV, L. A. N. AMARAL, A. L. GOLDBERGER, H. E. STANLEY, Stochastic feedback and the regulation of biological rhythms, Europhys. Lett., 43 (1998) 363-369. P. Ch. IVANOV, L. A. N. AMARAL, A. L. GOLDBERGER, S. HAVLIN, M. G. ROSENBLUM, Z. STRUZIK, H. E. STANLEY, Multifractality in human heartbeat dynamics, Nature, 399 (1999) 461-465.Google Scholar
  24. 24.
    M. Batty, P. Longley, Fractal Cities, San Diego: Academic Press, 1994. H. MAKSE, S. HAVLIN, H. E. STANLEY, Modeling urban growth patterns, Nature, 377 (1995) 608-612. X. GABAIX, Zipf's law for cities: An explanation, Quarterly J. Econ., 114 (1999) 739-767.Google Scholar
  25. 25.
    B. B. Mandelbrot, The variation of certain speculative prices, J. Business, 36 (1963) 394-419. A. PAGAN, The econometrics of financial markets, J. Empirical Finance, 3 (1996) 15-102. T. LUX, The stable paretian hypothesis and the frequency of large returns: An examination of major German stocks, Applied Financial Economics, 6 (1996) 463-475. U. A. MULLER, M. M. DACOROGNA, O. V. PICTET, Heavy tails in high-frequency financial data, in: A Practical Guide to Heavy Tails, edited by R. J. ADLER, R. E. FELDMAN, M. S. TAQQU, Birkhäuser Publishers, 1998, pp. 83-311. V. PLEROU, P. GOPIKRISHNAN, L. A. N. AMARAL, M. MEYER, H. E. STANLEY, Scaling of the distribution of price fluctuations of individual companies, Phys. Rev. E, 60 (1999) 6519-6529. P. GOPIKRISHNAN, V. PLEROU, L. A. N. AMARAL, M. MEYER, H. E. STANLEY, Scaling of the distributions of fluctuations of financial market indices, Phys. Rev. E, 60 (1999) 5305-5316.Google Scholar
  26. 26.
    U. A. Muller, M. M. Dacorogna, R. B. Olsen, O. V. Pictet, M. Schwarz, C. Morgenegg, Journal of Banking and Finance, 14 (1990) 1189-1195.Google Scholar
  27. 27.
    M. H. R. Stanley, L. A. N. Amaral, S. V. Buldyrev, S. Havlin, H. Leschhorn, P. Maass, M. A. Salinger, H. E. Stanley, Scaling behaviour in the growth of companies, Nature, 379 (1996) 804-806.Google Scholar
  28. 28.
    L. A. N. Amaral, S. V. Buldyrev, S. Havlin, H. Leschhorn, P. Maass, M. A. Salinger, H. E. Stanley, M. H. R. Stanley, Scaling behavior in economics: I. Empirical results for company growth, J. Phys. I France, 7 (1997) 621-633.Google Scholar
  29. 29.
    Y. Lee, L. A. N. Amaral, D. Canning, M. Meyer, H. E. Stanley, Universal features in the growth dynamics of complex organizations, Phys. Lev. Lett., 81 (1998) 3275-3278.Google Scholar
  30. 30.
    H. E. Stanley, Power laws and universality, Nature, 378 (1995) 554-555.Google Scholar
  31. 31.
    R. Gibrat, Les Inégalités Economiques, Sirey, Paris, 1931. Y. IJIRI, H. A. SIMON, Skew Distributions and the Sizes of Business Firms, North Holland, Amsterdam, 1977. B. H. HALL, The Relationship between firm size and firm growth in the U.S. manufacturing sector, The J. Indust. Econ., 35 (1987) 583-606. J. SUTTON, Gibrat's legacy, J. Econ. Lit., 35 (1997) 40-59.Google Scholar
  32. 32.
    V. Pareto, Cours d'Economie Politique, Lausanne and Paris, 1897. P. LÉVY, Théorie de l'Addition des Variables Aléatoires, Gauthier-Villars, Paris, 1937. G. K. ZIPF, Human Behavior and the Principle of Least Effort, Addison-Wesley, Cambridge MA, 1949. G. R. CARROLL, National city-size distribution: What do we know after 67 years of research? Progress in Human Geography, VI (1982) 1-43.Google Scholar
  33. 33.
    S. N. Durlauf, On the convergence and divergence of growth rates, The Economic J., 106 (1996) 1016-1018.Google Scholar
  34. 34.
    R. Summers, A. Heston, The Penn World Tables (Mark 5): An expanded set of international comparisons, 1950-1988, Quarterly J. Economics, 106 (1991) 327-368.Google Scholar
  35. 35.
    W. H. Press et al., Numerical Recipes, 2nd ed., Cambridge University Press, Cambridge, 1992.Google Scholar
  36. 36.
    J. Sutton, The Variance of Firm Growth Rates: The 'Scaling' Puzzle, Working paper, London School of Economics, 2000.Google Scholar
  37. 37.
    L. A. N. Amaral, S. V. Buldyrev, S. Havlin, M. A. Salinger, H. E. Stanley, Power law scaling for a system of interacting units with complex internal structure, Phys. Rev. Letters, 80 (1998) 1385-1388.Google Scholar
  38. 38.
    A. Chandler, Strategy and Structure, MIT Press, Cambridge, 1962.Google Scholar
  39. 39.
    M. Gort, Diversification and Integration in American Industry, Princeton University Press, Princeton, 1962.Google Scholar
  40. 40.
    B. Jovanovic, The diversification of production, Brookings Pap. Econ. Ac.: Microeconomics (1), VI (1993) 197-247.Google Scholar
  41. 41.
    National Science Foundation, Division of Science Resources Studies, Academic Research and Development Expenditures, NSF, Arlington VA, 1998.Google Scholar
  42. 42.
    United States University Science Indicators on Diskette, 1981–1997, Institute for Scientific Information, Philadelphia, 1998.Google Scholar
  43. 43.
    United States Patent and Trademarks Office Databases 1976–1997 [].Google Scholar
  44. 44.
    Higher Education Funding Council for England, The 1996 Research Assessment Exercise, HEFCE, Bristol, 1996.Google Scholar
  45. 45.
    Natural Sciences and Engineering Research Council of Canada, NSERC Grant Database for 1991–1998, NSERC, Ottawa, 1999.Google Scholar
  46. 46.
    H. F. Moed, M. Luwel, J. A. Houben, H. Van Den Berghe, E. Spruyt, Funding and research performance, Nature, 392 (1997) 119-120.Google Scholar

Copyright information

© Kluwer Academic Publishers/Akadémiai Kiadó 2001

Authors and Affiliations

  • Luis A. N. Amaral
    • 1
  • P. Gopikrishnan
    • 1
  • Kaushik Matia
    • 1
  • Vasiliki Plerou
    • 1
    • 2
  • H. E. Stanley
    • 1
  1. 1.Center for Polymer Studies and Department of PhysicsBoston UniversityBoston(USA)
  2. 2.Department of PhysicsBoston CollegeBoston(USA)

Personalised recommendations