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The Creative Development of Fields: Learning, Creativity, Paths, Implications

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  • Jonathan S. Feinstein

    (Yale School of Management)

Abstract

I present a model of the creative development of a field and analysis of the model based on an extensive set of simulations. A field as defined here is a domain for human activity and engagement, including for example standard academic fields as well as practical fields like law, medicine, design, and fields of technology. In the model in this paper, the field is defined in terms of the body of knowledge and elements or products that have been created in the field up to that point. The field begins from an initial state and grows as individuals enter the field and make new contributions; its basic structure resembles a lattice. New elements are created via combining preexisting elements, based on specific rules for combinations; thus I follow much of the creativity literature in defining creativity as creating novel conceptual combinations. The heart of the model is a rational, optimizing model of individual creative development, in which individuals have as their aim maximizing the expected value of their contribution to the field. An individual selects an initial set of elements in the field to learn, then gains intuitive signals about potentially fruitful new combinations based on this learning set, selects additional elements to learn, and finally chooses a potential new element to attempt to make. If the element is viable, it is added to the field, together with any subbundle elements co-created with it. The simulation analysis reveals a rich set of empirical predictions about the development of fields through this process. A first striking find is the diversity of possible paths of development starting from a given initial state. The intuitive signals individuals receive are an important factor in generating this diversity, as signals lead individuals to attempt to make elements they might otherwise not pursue, thus shaping the development of the field in important ways. The results also reveal a high degree of path dependence, generated as individuals build on the work of their predecessors, and interesting temporal patterns for how output in one period is linked with what occurred in the previous period.

Suggested Citation

  • Jonathan S. Feinstein, 2017. "The Creative Development of Fields: Learning, Creativity, Paths, Implications," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(1), pages 23-62, March.
  • Handle: RePEc:spr:jknowl:v:8:y:2017:i:1:d:10.1007_s13132-015-0277-0
    DOI: 10.1007/s13132-015-0277-0
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    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. Silverberg, Gerald & Verspagen, Bart, 2007. "The size distribution of innovations revisited: An application of extreme value statistics to citation and value measures of patent significance," Journal of Econometrics, Elsevier, vol. 139(2), pages 318-339, August.
    3. Bramoullé, Yann & Saint-Paul, Gilles, 2010. "Research cycles," Journal of Economic Theory, Elsevier, vol. 145(5), pages 1890-1920, September.
    4. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    5. Philippe Aghion & Christopher Harris & Peter Howitt & John Vickers, 2001. "Competition, Imitation and Growth with Step-by-Step Innovation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(3), pages 467-492.
    6. Jonathan S. Feinstein, 2011. "Optimal Learning Patterns for Creativity Generation in a Field," American Economic Review, American Economic Association, vol. 101(3), pages 227-232, May.
    7. Lee Fleming & Olav Sorenson, 2004. "Science as a map in technological search," Strategic Management Journal, Wiley Blackwell, vol. 25(8‐9), pages 909-928, August.
    8. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    9. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680.
    10. Samuel S. Kortum, 1997. "Research, Patenting, and Technological Change," Econometrica, Econometric Society, vol. 65(6), pages 1389-1420, November.
    11. Martin L. Weitzman, 1998. "Recombinant Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 331-360.
    12. Scherer, F. M. & Harhoff, Dietmar, 2000. "Technology policy for a world of skew-distributed outcomes," Research Policy, Elsevier, vol. 29(4-5), pages 559-566, April.
    13. Evenson, Robert E & Kislev, Yoav, 1976. "A Stochastic Model of Applied Research," Journal of Political Economy, University of Chicago Press, vol. 84(2), pages 265-281, April.
    14. Harhoff, Dietmar & Gambardella, Alfonso & Verspagen, Bart, 2008. "The Value of European Patents," CEPR Discussion Papers 6848, C.E.P.R. Discussion Papers.
    15. Luis Garicano, 2000. "Hierarchies and the Organization of Knowledge in Production," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 874-904, October.
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    Cited by:

    1. Broto Bhardwaj, 2019. "Role of Knowledge Management in Enhancing the Entrepreneurial Ecosystems Through Corporate Entrepreneurship and Strategic Intent in High-tech Firms," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(4), pages 1831-1859, December.
    2. Rodet, Cortney S., 2022. "Does cognitive load affect creativity? An experiment using a divergent thinking task," Economics Letters, Elsevier, vol. 220(C).

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