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Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics

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Abstract

Development of theoretically sound methods and strategies for informed science and innovation policy analysis is critically important to each nation's ability to benefit from R&D investments. Gaining deeper insight into complex social processes that influence the growth and formation of scientific fields and development over time of a diverse workforce requires a systemic and holistic view. A research agenda for the development of rigorous complex adaptive systems models is examined to facilitate the study of incentives, strategies, mobility, and stability of the science-based innovation ecosystem, while examining implications for the sustainability of a diverse science enterprise.

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  • Levent Yilmaz, 2011. "Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-2.
  • Handle: RePEc:jas:jasssj:2011-51-2
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    6. John Seely Brown & Paul Duguid, 1991. "Organizational Learning and Communities-of-Practice: Toward a Unified View of Working, Learning, and Innovation," Organization Science, INFORMS, vol. 2(1), pages 40-57, February.
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