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Island + Bridge: how transformative innovation is organized in the federal government

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  • Avery Sen

Abstract

Careful organization of research and development (R&D) is the key to transformative innovation. Among US federal R&D programs, the Defense Advanced Research Projects Agency (DARPA), the Advanced Research Projects Agency for Energy (ARPA-E), and the Advanced Technology Program (ATP) were designed to empower groups of people to tackle complex problems and realize broad societal benefits. This article offers a taxonomy of heuristics that guide the work of these three agencies, grounded in qualitative accounts of management practices. At the heart of each agency is the duality of isolation and interaction, or ‘Island’ and ‘Bridge’. The Island clusters heuristics that isolate R&D programs from the concerns of operations (as well as those of basic research). The Bridge clusters heuristics that connects R&D to broader institutional contexts. Island + Bridge is a framework for understanding a range of practices at organizations that aim to create radical change.

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  • Avery Sen, 2017. "Island + Bridge: how transformative innovation is organized in the federal government," Science and Public Policy, Oxford University Press, vol. 44(5), pages 707-721.
  • Handle: RePEc:oup:scippl:v:44:y:2017:i:5:p:707-721.
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    File URL: http://hdl.handle.net/10.1093/scipol/scx007
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    Cited by:

    1. Watson, Anna, 2022. "Designing publicly funded organisations for accelerated low carbon innovation: A case study of the ETI, UK and ARPA-E, US," Energy Policy, Elsevier, vol. 168(C).
    2. Nicolas Bunde & Nina Czernich & Oliver Falck & Clemens Fuest, 2020. "European public goods: The US ARPA system as a role model for promoting disruptive innovation in Europe?," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 117, October.
    3. Pierre Azoulay & Erica Fuchs & Anna P. Goldstein & Michael Kearney, 2018. "Funding Breakthrough Research: Promises and Challenges of the "ARPA Model"," NBER Chapters, in: Innovation Policy and the Economy, Volume 19, pages 69-96, National Bureau of Economic Research, Inc.
    4. Du, Jian & Li, Peixin & Haunschild, Robin & Sun, Yinan & Tang, Xiaoli, 2020. "Paper-patent citation linkages as early signs for predicting delayed recognized knowledge: Macro and micro evidence," Journal of Informetrics, Elsevier, vol. 14(2).

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