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A few special cases: scientific creativity and network dynamics in the field of rare diseases

Author

Listed:
  • M. Laura Frigotto

    (University of Trento)

  • Massimo Riccaboni

    (University of Trento)

Abstract

We develop a model of scientific creativity and test it in the field of rare diseases. Our model is based on the results of an in-depth case study of the Rett Syndrome. Archival analysis, bibliometric techniques and expert surveys are combined with network analysis to identify the most creative scientists. First, we compare alternative measures of generative and combinatorial creativity. Then, we generalize our results in a stochastic model of socio-semantic network evolution. The model predictions are tested with an extended set of rare diseases. We find that new scientific collaborations among experts in a field enhance combinatorial creativity. Instead, high entry rates of novices are negatively related to generative creativity. By expanding the set of useful concepts, creative scientists gain in centrality. At the same time, by increasing their centrality in the scientific community, scientists can replicate and generalize their results, thus contributing to a scientific paradigm.

Suggested Citation

  • M. Laura Frigotto & Massimo Riccaboni, 2011. "A few special cases: scientific creativity and network dynamics in the field of rare diseases," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 397-420, October.
    • Handle: RePEc:spr:scient:v:89:y:2011:i:1:d:10.1007_s11192-011-0431-9
    DOI: 10.1007/s11192-011-0431-9
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    1. Lee Fleming & David M. Waguespack, 2007. "Brokerage, Boundary Spanning, and Leadership in Open Innovation Communities," Organization Science, INFORMS, vol. 18(2), pages 165-180, April.
    2. Jason Owen-Smith & Massimo Riccaboni & Fabio Pammolli & Walter W. Powell, 2002. "A Comparison of U.S. and European University-Industry Relations in the Life Sciences," Management Science, INFORMS, vol. 48(1), pages 24-43, January.
    3. Lane, David & Malerba, Franco & Maxfield, Robert & Orsenigo, Luigi, 1996. "Choice and Action," Journal of Evolutionary Economics, Springer, vol. 6(1), pages 43-76, February.
    4. Orsenigo, L. & Pammolli, F. & Riccaboni, Massimo, 2001. "Technological change and network dynamics: Lessons from the pharmaceutical industry," Research Policy, Elsevier, vol. 30(3), pages 485-508, March.
    5. Martin L. Weitzman, 1998. "Recombinant Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 331-360.
    6. Bettencourt, Luís M.A. & Cintrón-Arias, Ariel & Kaiser, David I. & Castillo-Chávez, Carlos, 2006. "The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 513-536.
    7. Chen, Chaomei & Chen, Yue & Horowitz, Mark & Hou, Haiyan & Liu, Zeyuan & Pellegrino, Donald, 2009. "Towards an explanatory and computational theory of scientific discovery," Journal of Informetrics, Elsevier, vol. 3(3), pages 191-209.
    8. Rinia, E. J. & van Leeuwen, Th. N. & van Vuren, H. G. & van Raan, A. F. J., 1998. "Comparative analysis of a set of bibliometric indicators and central peer review criteria: Evaluation of condensed matter physics in the Netherlands," Research Policy, Elsevier, vol. 27(1), pages 95-107, May.
    9. Robin Cowan & Nicolas Jonard, 2003. "On the Workings of Scientific Communities," Chapters, in: Aldo Geuna & Ammon J. Salter & W. Edward Steinmueller (ed.), Science and Innovation, chapter 9, Edward Elgar Publishing.
    10. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    11. David W. Galenson & Bruce A. Weinberg, 2001. "Creating Modern Art: The Changing Careers of Painters in France from Impressionism to Cubism," American Economic Review, American Economic Association, vol. 91(4), pages 1063-1071, September.
    12. John D. Sterman & Jason Wittenberg, 1999. "Path Dependence, Competition, and Succession in the Dynamics of Scientific Revolution," Organization Science, INFORMS, vol. 10(3), pages 322-341, June.
    13. Luís M. A. Bettencourt & David I. Kaiser & Jasleen Kaur & Carlos Castillo-Chávez & David E. Wojick, 2008. "Population modeling of the emergence and development of scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 495-518, June.
    14. Bruckner, E & Ebeling, W & Jimenez Montano, M.A. & Scharnhorst, A., 1996. "Nonlinear Stochastic Effects of Substitution--An Evolutionary Approach," Journal of Evolutionary Economics, Springer, vol. 6(1), pages 1-30, February.
    15. Gino Cattani & Simone Ferriani, 2008. "A Core/Periphery Perspective on Individual Creative Performance: Social Networks and Cinematic Achievements in the Hollywood Film Industry," Organization Science, INFORMS, vol. 19(6), pages 824-844, December.
    16. N. Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, , vol. 2(2), pages 91-105, June.
    17. Carla Taramasco & Jean-Philippe Cointet & Camille Roth, 2010. "Academic team formation as evolving hypergraphs," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 721-740, December.
    18. Aldo Geuna & Ammon J. Salter & W. Edward Steinmueller (ed.), 2003. "Science and Innovation," Books, Edward Elgar Publishing, number 2831.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Creativity; Co-authorship network; Scientific collaboration; Bibliometric indicators; Biomedical research; Qualitative and quantitative method;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • L65 - Industrial Organization - - Industry Studies: Manufacturing - - - Chemicals; Rubber; Drugs; Biotechnology; Plastics
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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