Practical modern product development, specifically rapid, lean efforts to create new disrupting or specialized products, face constraints that require modified requirements elicitation (RE) techniques. Requirements elicitation conventions have not been updated to address the challenges of these approaches, and industry practitioners lack the tools to select the most efficient techniques. This study examines the RE approaches performed by three resource-limited teams conducting discontinuous new product development through a multi-case study to identify gaps between the literature and practice, with suggestions to fill them. Our findings suggest modern RE practices and challenges closely reflect those found by studies on RE in agile development, highlighted by a limited variety of techniques and a focus on user feedback despite user unavailability, resulting in partially complete and validated requirements. We suggest further investigation into practical technique selection, development of technique metrics, and a technique selection literature review to practitioners prior to RE.

This dissertation examines the role of public investments in inducing small firms to develop risky, early-stage technologies. It contributes to expanding our understanding of the consequences of research, innovation, and entrepreneurship policies and programs by investigating in more depth the effect of the Small Business Innovation Research (SBIR) program on the innovation effort, ability to attract external capital, and other metrics of post-entry performance of small business start-ups using a new sample and estimation approach. Unlike prior R&D subsidy studies that concentrated almost exclusively on European countries, this dissertation focused on small business start-ups in the United States using a new scientific survey of new firms. It integrated the Kauffman Firm Survey (KFS) from the Ewing Marion Kauffman Foundation with the SBIR recipient dataset from the U.S. Small Business Administration (SBA) and used advances in statistical matching to achieve better comparability between the treated and control groups of small business start-ups. The integrated KFS-SBA dataset, which contains both recipient and non-recipient small firms, and statistical matching allowed us to empirically construct the counterfactual outcomes of SBIR recipients. This dissertation balanced the pre-treatment characteristics of SBIR recipients and non-recipients through propensity score matching (PSM). It constructed the comparison sample by identifying non-recipients with nearly identical propensity scores as those of SBIR recipients. Consistent with the propensity score theorem, observations with the same distribution of propensity scores have the same distribution of observable characteristics. PSM made the comparison and treatment samples homogenous except in SBIR program exposure, making the fundamental assumption of ignorability of treatment assignment more plausible. Using the realized outcomes of observationally similar non-recipient start-ups as the counterfactual outcomes of SBIR recipients, we found empirical evidence of the input additionality effect of the SBIR program. Had they not applied for and granted SBIR R&D subsidies, recipient start-ups would have spent only $185,000 in R&D, but with SBIR their R&D effort was significantly increased to $663,000, on average. The treatment effects analyses also found a significant positive effect of SBIR on innovation propensity and employment. However, it appears that public co-financing of commercial R&D has crowded-out privately financed R&D of small business start-ups in the United States. A dollar of SBIR subsidy decreased firm-financed R&D by about $0.16. Contrary to prior SBIR studies, we did not find any significant "halo effect" or "certification effect" of receiving an SBIR award on attracting external capital. However, we discovered a different certification effect of the SBIR program: SBIR grantees are more likely to attract external patents. This finding also confirms that innovation requires a portfolio of internal and external knowledge assets as theorized by David Teece and his colleagues. This dissertation's empirical results may be relevant to the Small Business Administration, SBIR participating agencies, the U.S. Congress, other federal, state and local policymakers, small high-tech start-ups, and scholars in the field of science, technology, and innovation policy.

This dissertation examines the role of public investments in inducing small firms to develop risky, early-stage technologies. It contributes to expanding our understanding of the consequences of research, innovation, and entrepreneurship policies and programs by investigating in more depth the effect of the Small Business Innovation Research (SBIR) program on the innovation effort, ability to attract external capital, and other metrics of post-entry performance of small business start-ups using a new sample and estimation approach. This study integrated the Kauffman Firm Survey from the Ewing Marion Kauffman Foundation with the SBIR recipient dataset from the U.S. Small Business Administration and used advances in the micro-econometrics of program evaluation to empirically construct the counterfactual outcomes of SBIR recipients. We found empirical evidence of the input additionality effect of the SBIR program. The treatment effects analyses also found a significant positive effect of SBIR on innovation propensity and employment. However, it appears that public co-financing of commercial R&D has crowded-out privately financed R&D of small business start-ups in the United States. A dollar of SBIR subsidy decreased firm-financed R&D by about $0.16. Contrary to prior SBIR studies, we did not find any significant “halo effect” or “certification effect” of receiving an SBIR award on attracting external capital. What we discovered is a different certification effect of the SBIR program: SBIR grantees are more likely to attract external patents. This finding confirms that innovation requires a portfolio of internal and external knowledge assets as theorized by David Teece and his colleagues.