Follow the (Industry) Money – The Impact of Science Networks and Industry-to-University Contracts on Academic Patenting in Nanotechnology and Biotechnology

Beaudry, Catherine; Kananian, Ramine

doi:10.1080/13662716.2013.791125

Cited by 24 publications

(33 citation statements)

References 61 publications

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“…These results suggest some level of review validity, although it is still unclear how and to what extent the funding can promote patent creation. It may be the direct effect is small; while some have observed small positive impacts on patent generation (Payne and Siow, 2003) or on patent originality and impact (Huang et al, 2006;Guerzoni et al, 2014), some have found no effect or even a negative effect (Sanyal, 2003;Beaudry and Kananian, 2013). Thus, patent productivity has some promise for use in tests of review validity, however future studies will likely require more subtle, nuanced approaches.…”

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confidence: 99%

External Tests of Peer Review Validity Via Impact Measures

Gallo

Glisson

2018

Front. Res. Metr. Anal.

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Peer review is used commonly across science as a tool to evaluate the merit and potential impact of research projects and make funding recommendations. However, potential impact is likely to be difficult to assess ex-ante; some attempts have been made to assess the predictive accuracy of these review decisions using impact measures of the results of the completed projects. Although many outputs, and thus potential measures of impact, exist for research projects, the overwhelming majority of evaluation of research output is focused on bibliometrics. We review the multiple types of potential impact measures with an interest in their application to validate review decisions. A review of the current literature on validating peer review decisions with research output impact measures is presented here; only 48 studies were identified, about half of which were US based and sample size per study varied greatly. 69% of the studies employed bibliometrics as a research output. While 52% of the studies employed alternative measures (like patents and technology licensing, post-project peer review, international collaboration, future funding success, securing tenure track positions, and career satisfaction), only 25% of all projects used more than one measure of research output. Overall, 91% of studies with unfunded controls and 71% of studies without such controls provided evidence for at least some level of predictive validity of review decisions. However, several studies reported observing sizable type I and II errors as well. Moreover, many of the observed effects were small and several studies suggest a coarse power to discriminate poor proposals from better ones, but not amongst the top tier proposals or applicants (although discriminatory ability depended on the impact metric). This is of particular concern in an era of low funding success, where many top tier proposals are unfunded. More research is needed, particularly in integrating multiple types of impact indicators in these validity tests, as well as considering the context of the research outputs relative to goals of the research program and concerns for reproducibility, translatability and publication bias. In parallel, more research is needed focusing on the internal validity of review decision making procedures and reviewer bias.Keywords: research funding, peer review, impact metrics, validity, grant GRANT PEER REVIEW AND IMPACT ASSESSMENTMost would generally agree the purpose of biomedical research is to advance knowledge for societal benefit, with the hope of favorably impacting disease outcomes and improving global health. Indeed, the National Institutes of Health (NIH ), the world's largest funder of biomedical research, characterizes their mission as to "seek fundamental knowledge about the nature and Gallo and GlissonReview Validity via Impact Measures behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability" (NIH, 2017). To help select which research projects to fund to achieve...

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confidence: 99%

External Tests of Peer Review Validity Via Impact Measures

Gallo

Glisson

2018

Front. Res. Metr. Anal.

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“…Interestingly, the more scientists work with industry, the more they bypass their technology transfer office when patenting (Goel and Göktepe-Hultén, 2018), meaning these patents are assigned to an external entity and not their university -a phenomenon highlighted by a recent study of a UK research university . Finally, having been contracted by a firm in the past positively influences patenting volume and quality for Quebecois academics (Beaudry and Kananian, 2013) and spending time collaborating with industry positively influences the propensity of US academics to patent and commercialise within those collaborations (Libaers, 2017), although yet again in both cases the relationship shows an inverse U-shape. However, Bikard et al (2019) provide a dissenting result using international data, suggesting that academics who work with industry patent less than comparable colleagues not working with industry; they suggest that this may be due to the fact that mixed academia-industry teams establish a division of labour where academics focus on publishing while industry partners focus on patenting.…”

Section: Commercial Consequencesmentioning

confidence: 97%

Academic Engagement: A Review of the Literature 2011-2019

Perkmann¹,

Salandra

Tartari

et al. 2019

SSRN Journal

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We provide a systematic review of the literature on academic engagement from 2011 onwards, which was the cutoff year of a previous review article published in Research Policy. Academic engagement refers to knowledge-related interactions of academic scientists with external organisations. It includes activities such as collaborative research with industry, contract research, consulting and informal ties. We consolidate what is known about the individual, organisational and institutional antecedents of academic engagement, and its consequences for research, commercialisation, and society at large. Our results suggest that individual characteristics associated with academic engagement include being scientifically productive, senior, male, locally trained, and commercially experienced. Academic engagement is also socially conditioned by peer effects and disciplinary characteristics. In terms of consequences, academic engagement is positively associated with academics' subsequent scientific productivity. We propose new areas of investigation where evidence remains inconclusive, including individual life cycle effects, the role of organisational contexts and incentives, cross-national comparisons, and the impact of academic engagement on the quality of subsequent research as well as the educational, commercial and society-wide impact.

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“…Often collaborations connect individual scholars far beyond their own teams and organizations. Consequently, innovation and technological change in nanotechnology emerge from efforts of scholarly networks rather than from individual efforts (Beaudry and Kananian 2013;Powell et al 1996). Its potential can be only realized in world-wide international and inter-organizational collaboration networks (Pandza et al 2011).…”

Section: Characteristics and Potential Of Nanotechnologymentioning

confidence: 99%

Formation and output of collaborations: the role of proximity in German nanotechnology

2019

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The development and deployment of technologies depend upon collaborations concurrently relying on proximity between partners. By employing publication data of German nanotechnology, we augment former findings on the relationship between proximity and collaboration in three ways. First, we shed light on how the various forms of proximity affect different stages of collaboration. Particularly, we split geographical proximity into pure physical and systemic proximity. By doing so, we can show that pure physical proximity plays a role early on, as it positively influences the formation of collaborations. In contrast, systemic proximity affects collaborations later on by inducing higher output. Second, innovation systems shape collaboration networks. We learn that specific features of publicly funded German research organizations influence the formation and output of collaborations via organizational proximity or a lack thereof. Third, cognitive proximity has by far the strongest magnitude of effect on both the formation and the output of collaborations. Particularly, existing partnership being cognitively diverse have a lot of potential. Therefore, research policy and university management might consider to stimulating current partnerships, being cognitively different.

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Follow the (Industry) Money – The Impact of Science Networks and Industry-to-University Contracts on Academic Patenting in Nanotechnology and Biotechnology

Cited by 24 publications

References 61 publications

External Tests of Peer Review Validity Via Impact Measures

External Tests of Peer Review Validity Via Impact Measures

Academic Engagement: A Review of the Literature 2011-2019

Formation and output of collaborations: the role of proximity in German nanotechnology

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