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Benchmarking university technology transfer performance with external research funding: a stochastic frontier analysis

Jason Coupet () and Yuhao Ba ()
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Jason Coupet: North Carolina State University
Yuhao Ba: North Carolina State University

The Journal of Technology Transfer, 2022, vol. 47, issue 2, No 11, 605-620

Abstract: Abstract Many universities engage in academic entrepreneurship, often with funding from external sources. Benchmarking technology transfer performance with external research funding can help universities identify and learn from peers that may possess strategic advantages in productivity. It also can be key for organizational learning and for communicating organizational performance to policy stakeholders and industry partners. In this study, we construct a unique dataset by linking two important data sources, AUTM and UMETRICS, and use stochastic frontier analysis to benchmark university licensing and revenue performance with different federal funding streams. Our empirical results suggest that universities looking to promote commercialization performance might look to National Science Foundation funding, and the universities best at production (i.e., licensing technologies and generating patents) with external funding are not necessarily the best at capturing benefits from generating revenue from entrepreneurial activity and launching start-ups. Our study points to the importance of the differential advantages of sources of federal research funding and offers implications for policy makers and university administrators.

Keywords: Performance; Federal funding; National science foundation; Benchmarking; Stochastic frontier analysis; D24; I23; O32; O38 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10961-021-09856-3

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The Journal of Technology Transfer is currently edited by Albert N. Link, Donald S. Siegel, Barry Bozeman and Simon Mosey

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