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on Innovation |
| By: | Chowdhury, Farhat (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics); Royalty, Anne (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | This paper presents a systematic empirical study of covariates associated with the success of NIH Phase I SBIR-funded research projects, where success is defined in terms of the small, entrepreneurial firm conducting the Phase I research subsequently receiving a follow-on Phase II research award. We find that women-owned firms are especially disadvantaged in this regard. Our findings suggest that SBIR program managers consider recommendations to overcome these disadvantages. Our recommendations could enhance the rate at which follow-on Phase II research projects are funded and possibly the rate at which the developed technologies are commercialized. |
| Keywords: | Small Business Innovation Research (SBIR) program; entrepreneurship; gender; program management; public sector; Phase I and Phase II research; technology development |
| JEL: | L38 O32 O38 |
| Date: | 2023–08–22 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2023_005&r=ino |
| By: | Ajay K. Agrawal; John McHale; Alexander Oettl |
| Abstract: | We model a key step in the innovation process, hypothesis generation, as the making of predictions over a vast combinatorial space. Traditionally, scientists and innovators use theory or intuition to guide their search. Increasingly, however, they use artificial intelligence (AI) instead. We model innovation as resulting from sequential search over a combinatorial design space, where the prioritization of costly tests is achieved using a predictive model. We represent the ranked output of the predictive model in the form of a hazard function. We then use discrete survival analysis to obtain the main innovation outcomes of interest – the probability of innovation, expected search duration, and expected profit. We describe conditions under which shifting from the traditional method of hypothesis generation, using theory or intuition, to instead using AI that generates higher fidelity predictions, results in a higher likelihood of successful innovation, shorter search durations, and higher expected profits. We then explore the complementarity between hypothesis generation and hypothesis testing; potential gains from AI may not be realized without significant investment in testing capacity. We discuss the policy implications. |
| JEL: | O31 O33 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31558&r=ino |
| By: | Link, Albert (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | Homophily studies have tended to focus on gender and race. Albeit that these comparisons are important, a focus on ethnic group relationships is conspicuously absent in the literature. In an effort to begin to fill this void, homophilic ethnic relationships among firm owners and publicly funded research project principal investigators is considered in this paper. Using data on Small Business Innovation Research (SBIR) program funded projects and Small Business Technology Transfer (STTR) program-funded projects, we find that the performance enhancing benefit of a homophilic relationship is dependent on the area of technology research. To the extent that the area of technology research is reflected in terms of the federal agency funding the research project, Department of Defense-funded projects are less enhanced by homophilic relationships than are research projects funded by other federal agencies. |
| Keywords: | homophily; SBIR; STTR; project R&D; program performance; |
| JEL: | H41 O22 O31 |
| Date: | 2023–08–22 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2023_006&r=ino |
| By: | Hayter, Christopher (Georgia Institute of Technology); Link, Albert (University of North Carolina at Greensboro, Department of Economics); Schaffer, Matthew (Eastern Michigan University) |
| Abstract: | Though academic entrepreneurship has long been associated with technology transfer and more broadly with the passage of the 1980 Bayh-Dole Act in 1980, we have little understanding of its emergence as a research field. This paper therefore investigates development of the concept of academic entrepreneurship by studying the use of related keywords in the titles of papers published in the Journal of Technology Transfer (JTT) beginning with volume 1 in 1977. We conclude from our empirical findings that the role of universities in technology transfer has been consistently emphasized in the titles of papers published in the JTT over time, with entrepreneurship emerging more recently as a crucial area of scholarly focus. |
| Keywords: | academic entrepreneurship; entrepreneurial university; technology transfer; project evaluation; research portfolio choices; |
| JEL: | G11 H40 L26 O33 |
| Date: | 2023–08–22 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2023_004&r=ino |
| By: | Yael Hochberg; Ali Kakhbod; Peiyao Li; Kunal Sachdeva |
| Abstract: | Implementing a state-of-the-art machine learning technique for causal identification from text data (C-TEXT), we document that patents authored by female inventors are under-cited relative to those authored by males. Relative to what the same patent would be predicted to receive had the lead inventor instead been male, patents with a female lead inventor receive 10% fewer citations. Patents with male lead inventors tend to undercite past patents with female lead inventors, while patent examiners of both genders appear to be more even-handed in the citations they add to patent applications. For female inventors, market-based measures of patent value load significantly on the citation counts that would be predicted by C-TEXT, but do not load significantly on actual forward citations. The under-recognition of female-authored patents likely has implications for the allocation of talent in the economy. |
| JEL: | C13 J16 J24 J71 O30 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31592&r=ino |
| By: | Fons-Rosen, Christian (University of California, Merced); Gaule, Patrick (University of Bristol); Hrendash, Taras (CERGE-EI) |
| Abstract: | We investigate the causes and consequences of the aging of the scientific workforce. Using novel data on the population of US chemistry faculty members over fifty years, we find that the secular increase in the age of the academic workforce has been mainly driven by the slowdown in faculty hiring combined with later retirements. By contrast, changes in the age at which scientists start their careers only contribute to about 20% of aging. Hiring more new faculty members could rejuvenate the scientific workforce and boost scientific productivity. |
| Keywords: | aging, science, universities, knowledge production |
| JEL: | O31 J24 J26 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16365&r=ino |
| By: | Meißner, Leonie; Peterson, Sonja; Semrau, Finn Ole |
| Abstract: | In a race against excessive global warming, the world must accelerate the development and adoption of environmental innovations (EIs). EIs are crucial in decarbonizing the economy and meeting the netzero targets. In this literature review, we delve into the role of governments in promoting EIs across stages of maturity and the likeliness of such support to reduce emissions and mitigation costs. Various theoretical justifications, such as knowledge externalities, dynamic increasing returns, path dependency and incomplete information, highlight the necessity to promote EI through governmental Research and Development (R&D) support. While emission pricing remains the most cost-efficient climate policy, it fails as a stand-alone instrument to sufficiently encourage EI. Accordingly, the optimal approach is a policy mix complementing emission pricing with governmental R&D support. The theoretical finding is backed by empirical studies on the development and deployment of renewable energies, which also show that investment in R&D can effectively reduce emissions and mitigation costs. By combining theoretical and empirical research, the review concludes by examining two pivotal policy actions aimed at accelerating the take-off of EIs: The US Inflation Reduction Act and the European Green New Deal Industrial Plan. We evaluate their specific aspects and limitations to effectively and efficiently contribute to decarbonization. |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwkwp:2254&r=ino |
| By: | Oliver Falck; Akash Kaura |
| Abstract: | For all its perennial focus on traditional industries, Germany has done a remarkable job in greening its manufacturing Green skills are quickly gaining prominence Automotive manufacturing is leading the way Germany is still a hotbed of innovation, but cannot afford to become complacent |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:econpb:_55&r=ino |
| By: | OECD |
| Abstract: | This report analyses the career options of doctoral and postdoctoral researchers. It identifies policies and practices to promote diverse careers, flexible career trajectories and ultimately better-quality research and innovation across different economic and social sectors. The report presents a conceptual framework and synthesis of available data and policy information. It offers recommendations and a set of policy options to: promote engagement and interaction with employers outside academia; provide researchers with experience and skills for diverse careers; encourage valorisation of diverse career options; support career development and guidance for researchers; promote inter-sectoral mobility; and, reconfigure and support careers in academia. |
| Date: | 2023–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaac:158-en&r=ino |