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Informational Complexity and the Flow of Knowledge across social boundaries

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  • Olav Sorenson

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  • Jan W. Rivkin
  • Lee Fleming

Abstract

Scholars from a variety of backgrounds – economists, sociologists, strategists, and students of technology management – have sought a better understanding of why some knowledge disperses widely while other knowledge does not. In this quest, some researchers have focused on the characteristics of the knowledge itself (e.g., Polanyi, 1966; Reed and DeFillippi, 1990; Zander and Kogut, 1995) while others have emphasized the social networks that constrain and enable the flow of knowledge (e.g., Coleman et al., 1957; Davis and Greve, 1997). This chapter examines the interplay between these two factors. Specifically, we consider how the complexity of knowledge and the density of social relations jointly influence the movement of knowledge. Imagine a social network composed of patches of dense connections with sparse interstices between them. The dense patches might reflect firms, for instance, or geographic regions or technical communities. When does knowledge diffuse within these dense patches circumscribed by social boundaries but not beyond them? Synthesizing social network theory with a view of knowledge transfer as a search process, we argue that knowledge inequality across social boundaries should reach its peak when the underlying knowledge is of moderate complexity. To test this hypothesis, we analyze patent data and compare citation rates across three types of social boundaries: within versus outside the firm, geographically near to versus far from the inventor, and internal versus external to the technological class. In all three cases, the disparity in knowledge diffusion across these borders is greatest for knowledge of an intermediate level of complexity.

Suggested Citation

  • Olav Sorenson & Jan W. Rivkin & Lee Fleming, 2005. "Informational Complexity and the Flow of Knowledge across social boundaries," Papers in Evolutionary Economic Geography (PEEG) 0511, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2005.
  • Handle: RePEc:egu:wpaper:0511
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    File URL: http://econ.geo.uu.nl/peeg/peeg0511.pdf
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    References listed on IDEAS

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    1. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    2. Koen Frenken & Alessandro Nuvolari, 2004. "The early development of the steam engine: an evolutionary interpretation using complexity theory," Industrial and Corporate Change, Oxford University Press, vol. 13(2), pages 419-450, April.
    3. S.A. Lippman & R.P. Rumelt, 1982. "Uncertain Imitability: An Analysis of Interfirm Differences in Efficiency under Competition," Bell Journal of Economics, The RAND Corporation, vol. 13(2), pages 418-438, Autumn.
    4. Fleming, Lee & Sorenson, Olav, 2001. "Technology as a complex adaptive system: evidence from patent data," Research Policy, Elsevier, vol. 30(7), pages 1019-1039, August.
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    Keywords

    evolutionary economics; informational complexity; knowledge flow; social boundaries;

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