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A Few Special Cases: Scientific Creativity and Network Dynamics in the Field of Rare Diseases

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  • Massimo Riccaboni
  • Maria Laura Frigotto

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, alternative measures of generative and combinatorial creativity are compared. Then, we generalize our results and present a stochastic model of socio-semantic network evolution. The model predictions are tested with multiple networks of rare disease specialties. 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 extending 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

  • Massimo Riccaboni & Maria Laura Frigotto, 2011. "A Few Special Cases: Scientific Creativity and Network Dynamics in the Field of Rare Diseases," DISA Working Papers 2011/03, Department of Computer and Management Sciences, University of Trento, Italy, revised 24 May 2011.
  • Handle: RePEc:trt:disawp:2011/03
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    References listed on IDEAS

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    1. 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.
    2. Lane, David & Malerba, Franco & Maxfield, Robert & Orsenigo, Luigi, 1996. "Choice and Action," Journal of Evolutionary Economics, Springer, vol. 6(1), pages 43-76, February.
    3. 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.
    4. Martin L. Weitzman, 1998. "Recombinant Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 113(2), pages 331-360.
    5. 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.
    6. Nigel Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, Sociological Research Online, vol. 2(2), pages 1-3.
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    8. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    9. 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.
    10. 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.
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    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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