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On the failure of scientific research: an analysis of SBIR projects funded by the U.S. National Institutes of Health

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Abstract

The Small Business Innovation Research (SBIR) program is the primary source of public funding in the United States for research by small firms on new technologies, and the National Institutes of Health (NIH) is a major contributor to that funding agenda. Although previous research has explored the determinants of research success for NIH SBIR projects, little is known about the determinants of project failure. This paper provides important, new evidence on the characteristics of NIH SBIR projects that fail. Specifically, we find that firms that have a founder with a business background are less likely to have their funded projects fail. We also find, after controlling for the endogenous nature of woman-owned firms, that such firms are also less likely to fail.

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Notes

  1. See https://sbir.nih.gov/statistics/award-data. The SBIR program supported by NIH is the second largest SBIR program in the United States, second only to that supported by the Department of Defense.

  2. Following Leyden and Link (2015) and Nightingale (1998), we think of science, the precursor to new technology, as the search for new knowledge; the search is based on observed facts and truths. Science begins with known starting conditions and searches for unknown end results. As defined, science is shrouded in uncertainty because the end results are unknown. We think of new technology as the application of knowledge, learned through science, to some known problem.

  3. For the legislative background on the SBIR program see Link and Link (2009), Link and Scott (2010, 2013), and Leyden and Link (2015a).

  4. Phase I awards were originally capped at $50,000; the current upper bound is $150,000.

  5. Phase II awards were originally capped at $500,000; the current upper bound is $1 million.

  6. Eleven agencies currently participate in the SBIR program: Environmental Protection Agency (EPA), National Aeronautics and Space Administration (NASA), National Science Foundation (NSF), and the Departments of Agriculture (USDA), Commerce (DoC), Defense (DoD), Education (ED), Energy (DOE), Health and Human Services (HHS, particularly NIH), Transportation (DoT), and most recently the Department of Homeland Security (DHS). The NRC study focused on the five largest SBIR programs; those at DoD, NIH, DOE, NASA, and NSF.

  7. Allen et al. (2012) develop a model that shows for the benefit-to-cost ratio associated with NIH’s program to equal unity, the elasticity of demand for commercialized projects from that program would have to be greater than 50. This implies, for any reasonable value of the elasticity of demand for a new technology, the resulting benefit-to-cost ratio would be extraordinarily large.

  8. Projects funded in 2001 were implicitly given four years to complete the Phase II research and enter into or even complete Phase III. Thus, projects funded in 2001 were ithe last cohort of projects considered by the NRC for the 2005 survey.

  9. This argument traces to Stinchcombe (1965).

  10. A recent application of this human capital argument had been offered by Sauser et al. (2009) in terms of the success, or lack thereof, of the Mars Climate Orbiter.

  11. The sample of 495 projects is a random sample of all NIH SBIR awards from 1992 through 2001. The mean SBIR award amount in the sample of 495 projects is $676.82 thousand ($2009). Following Jankowski (1993), award amounts were adjusted to $2009 by the GDP deflator. The mean SBIR amount in the sample of 461 projects is $690.28 thousand ($2009). However, the latter mean is not significantly different than the mean award amount from the random sample of 495 projects (t = 1.34, Pr > |t| = 0.182). Thus, we refer to the sample of 461 projects as a random sample representative of Phase II projects over the relevant time period.

  12. The relatively small sample size of our data relative to the number of centers and institutes represented does not support controlling for every center and institute represented. We explored controlling for additional centers and institutes and grouping centers and institutes in a variety of combinations. We found that our primary results were not sensitive to the specification of the center and institute controls.

  13. The 1992 reauthorization also emphasized minority ownership. Although we have information on minority ownership, the prevalence of minority ownership in our data is too low to allow a rigorous analysis of minority ownership. To assess the sensitivity of our results, we estimated all econometric models including minority ownership as an exogenous determinant of failure and found that it did not qualitatively change our results.

  14. Link and Wright (2015) explored the statistical relationship between project failure and gender of firm ownership using combined SBIR data from DoD, NIH, DOE, NASA, and NSF. Their single-equation analysis did not address the endogenous nature of woman-owned firms. Our analysis not only overcomes that econometric shortcoming, but also because of our focus on NIH-funded projects we are able to hold constant center and institute effects.

  15. We used Stata version 13 for our estimation.

  16. These institute controls were chosen based on our perception that NIAAA, NIDA, NIMH, and NICHD were, relative to the other institutes in our data, more likely to fund “service” technologies (e.g., novel behavioral therapies or educational programs) as opposed to “manufacturing” technologies (i.e., pharmaceutical compounds or medical devices). As this reasoning is admittedly ad hoc, we explored other sets of controls for centers and institutes in Z following the same approach we used to explore controls in X. Our primary results are not sensitive to the specific controls used.

  17. See Wright and Link (2015) who also find that woman-owned firms have a lower probability of failure.

  18. The marginal effect of buss was calculated as the difference in the predicted probability of failure associated with changing buss from 0 to 1, holding all other covariates fixed.

  19. Link (2015) discusses the myriad ways that university resources are used by firms in their SBIR research projects.

  20. We thank an anonymous reviewer for suggesting that our findings that women-owned firms have a lower probability of project failure may not be independent of the relationship between the funded project and university involvement in the project. To the extent that it is the case that women-owned firms have a greater likelihood of partnering with university faculty who indend to create a spin-off venture, then the negative relationship between womanown and failure may not be correctly specified in our model, although the data needed for a more complete specification are not available. See Hayter (2011, 2015) for insight about university spin-offs. Future research in this area might explore this issue.

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Correspondence to Albert N. Link.

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Andersen, M.S., Bray, J.W. & Link, A.N. On the failure of scientific research: an analysis of SBIR projects funded by the U.S. National Institutes of Health. Scientometrics 112, 431–442 (2017). https://doi.org/10.1007/s11192-017-2353-7

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