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Evaluating the tail of the distribution: the economic contributions of frequently awarded government R&D recipients

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  • Feldman, Maryann
  • Johnson, Evan E.
  • Bellefleur, Remi
  • Dowden, Savannah
  • Talukder, Eshika

Abstract

Government R&D programs are intended to assist in the commercialization of technology and provide for the greater public good. Among the primary instruments for this type of government action are competitive grants for small, high-tech businesses. However, there is a perception among scholars and administrators that a small number of firms receive a large number of awards without furthering government objectives. The term mill is a less than complimentary term used to reference a firm that receives multiple government R&D awards. The criticism is based on a belief that this group of firms do not advance innovative technologies and do not serve the needs of the awarding agency. As a result, there are attempts to limit the number of awards that firms receive, with limited consideration of the firms themselves and the role they play in the larger innovation system. We specifically examine the U.S. Small Business Innovation Research (SBIR) program, focusing on a group of firms at the extreme tail of the distribution of awards. We consider the business model employed by these firms, their patenting and licensing behavior, and the products they introduce to the market. We also consider their impacts as incubators of spinoff firms, research environments that augment human capital, and suppliers to government through procurement.

Suggested Citation

  • Feldman, Maryann & Johnson, Evan E. & Bellefleur, Remi & Dowden, Savannah & Talukder, Eshika, 2022. "Evaluating the tail of the distribution: the economic contributions of frequently awarded government R&D recipients," Research Policy, Elsevier, vol. 51(7).
  • Handle: RePEc:eee:respol:v:51:y:2022:i:7:s004873332200066x
    DOI: 10.1016/j.respol.2022.104539
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    1. Feldman, Maryann & Fleming, Lee & Heaton, Sohvi & Desai, Sameeksha & Teece, David, 2022. "Uncommon methods and metrics for local entrepreneurial ecosystems," Research Policy, Elsevier, vol. 51(9).

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