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Models of growth in organizational ecology: a simulation assessment

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  • J. Richard Harrison

Abstract

Organizational ecologists investigate the dynamics of organizational populations. Ecological analysis has focused explicitly on organizational founding and mortality processes in these populations with notable success, but has lagged behind in its understanding of organizational growth, which plays an important role in ecological processes. Using computer simulation analysis, this paper examines four models for organizational growth: Gibrat's law, a proportional growth model; an extension of Gibrat's law that includes density and age effects on growth; a Schumpeterian growth model based on R&D investment; and a demographic growth model based on Poisson processes for the arrival and departure of individuals. The simulation findings are compared with empirical observations, and the implications of the findings for modeling organizational growth are discussed. In particular, I argue that it is unlikely that 'one growth model fits all', and suggest that separate growth models need to be developed for different industrial and organizational contexts. Copyright 2004, Oxford University Press.

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  • J. Richard Harrison, 2004. "Models of growth in organizational ecology: a simulation assessment," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(1), pages 243-261, February.
  • Handle: RePEc:oup:indcch:v:13:y:2004:i:1:p:243-261
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    Cited by:

    1. Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    2. Mukti Khaire, 2010. "Young and No Money? Never Mind: The Material Impact of Social Resources on New Venture Growth," Organization Science, INFORMS, vol. 21(1), pages 168-185, February.
    3. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 227-244, October.
    4. Michael I.C. Nwogugu, 2019. "Complex Systems, Multi-Sided Incentives and Risk Perception in Companies," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-44704-3, December.

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