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Standing on Academic Shoulders: Measuring Scientific Influence in Universities

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  • James D. Adams
  • J. Roger Clemmons
  • Paula E. Stephan

Abstract

This article measures scientific influence by means of citations to academic papers. The data source is the Institute for Scientific Information (ISI); the scientific institutions included are the top 110 U.S. research universities; the 12 main fields that classify the data cover nearly all of science; and the time period is 1981-1999. Altogether the database includes 2.4 million papers and 18.8 million citations. Thus the evidence underlying our findings accounts for much of the basic research conducted in the United States during the last quarter of the 20th century. This research in turn contributes a significant part of knowledge production in the U.S. during the same period. The citation measure used is the citation probability, which equals actual citations divided by potential citations, and captures average utilization of cited literature by individual citing articles. The mean citation probability within fields is on the order of 10-5. Cross-field citation probabilities are one-tenth to one-hundredth as large, or 10-6 to 10-7. Citations between pairs of citing and cited fields are significant in less than one-fourth of the possible cases. It follows that citations are largely bounded by field, with corresponding implications for the limits of scientific influence. Cross-field citation probabilities appear to be symmetric for mutually citing fields. Scientific influence is asymmetric within fields, and occurs primarily from top institutions to those less highly ranked. Still, there is significant reverse influence on higher-ranked schools. We also find that top institutions are more often cited by peer institutions than lower-ranked institutions are cited by their peers. Overall the results suggest that knowledge spillovers in basic science research are important, but are circumscribed by field and by intrinsic relevance. Perhaps the most important implication of the results are the limits that they seem to impose on the returns to scale in the knowledge production function for basic research, namely the proportion of available knowledge that spills over from one scientist to another.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 10875.

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Date of creation: Nov 2004
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Publication status: published as James ADAMS & J. Roger CLEMMONS & Paula E. STEPHAN, 2005. "Standing on Academic Shoulders: Measuring Scientific Influence in Universities," Annales d'Economie et de Statistique, ENSAE, issue 79-80, pages 61-90.
Handle: RePEc:nbr:nberwo:10875

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References

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  1. Adams, James D, 1990. "Fundamental Stocks of Knowledge and Productivity Growth," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 673-702, August.
  2. Audretsch, David B & Stephan, Paula E, 1996. "Company-Scientist Locational Links: The Case of Biotechnology," American Economic Review, American Economic Association, vol. 86(3), pages 641-52, June.
  3. Zucker, Lynne G & Darby, Michael R & Brewer, Marilynn B, 1998. "Intellectual Human Capital and the Birth of U.S. Biotechnology Enterprises," American Economic Review, American Economic Association, vol. 88(1), pages 290-306, March.
  4. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages S71-102, October.
  5. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45 National Bureau of Economic Research, Inc.
  6. Manuel Trajtenberg, 1990. "A Penny for Your Quotes: Patent Citations and the Value of Innovations," RAND Journal of Economics, The RAND Corporation, vol. 21(1), pages 172-187, Spring.
  7. David, Paul A, 1998. "Common Agency Contracting and the Emergence of "Open Science" Institutions," American Economic Review, American Economic Association, vol. 88(2), pages 15-21, May.
  8. Wesley M. Cohen & Richard R. Nelson & John P. Walsh, 2002. "Links and Impacts: The Influence of Public Research on Industrial R&D," Management Science, INFORMS, vol. 48(1), pages 1-23, January.
  9. Adam B. Jaffe, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits and Market Value," NBER Working Papers 1815, National Bureau of Economic Research, Inc.
  10. Michael R. Darby & Lynne G. Zucker, 2003. "Grilichesian Breakthroughs: Inventions of Methods of Inventing and Firm Entry in Nanotechnology," NBER Working Papers 9825, National Bureau of Economic Research, Inc.
  11. David Popp, 2002. "Induced Innovation and Energy Prices," American Economic Review, American Economic Association, vol. 92(1), pages 160-180, March.
  12. Marie Thursby & Richard Jensen, 2001. "Proofs and Prototypes for Sale: The Licensing of University Inventions," American Economic Review, American Economic Association, vol. 91(1), pages 240-259, March.
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Cited by:
  1. James D. Adams & J. Roger Clemmons, 2006. "Science and Industry: Tracing the Flow of Basic Research through Manufacturing and Trade," Rensselaer Working Papers in Economics 0614, Rensselaer Polytechnic Institute, Department of Economics.
  2. Hans Lööf & Anders Broström, 2008. "Does knowledge diffusion between university and industry increase innovativeness?," The Journal of Technology Transfer, Springer, vol. 33(1), pages 73-90, February.

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