Measuring the success (or efficiency) of technology transfer by using the revenue generated through the deals signed by universities may not be the best metric. Sometimes, there is a very big outlier that amounts to the majority of the money received by universities (imagine being at the other end of the Google licensing). In @vinig2015Measuring the performance of university technology transfer using meta data approach: the case of Dutch universities they propose using the total number of Patents, Licenses and Spin-Offs as a metric for technology-transfer. However, this should be normalized, and the authors suggest using the total number of published papers (on a given year), as the normalization factor.
With this approach, the authors observe that MIT and Stanford are more efficient transferring technology than, for example, the university of Leiden (the paper is centered on Dutch universities exclusively). The paper has some mistakes (number wrongly added) and some methodological concerns: For example, they are obsessed calculating the 1%, 2%, 3% as the factor for the total number of published papers, which adds zero extra knowledge to their work. They also fail to disclose how they calculated the numbers of published papers for the MIT and Stanford.
What I think worries me the most is that they don’t give any thoughts to the fact of having patents with equal weight to licenses and spin-offs. Patenting is, fundamentally, a process of throwing money at a problem. But they don’t generate any value in themselves. In their tables, there are universities with more patents than licenses, or the opposite. They don’t discuss whether the licenses are related to those patents or not.
Therefore, I believe there should be a weighted average of tech transfer output item, not the plain addition. Also, comparing only to MIT and Stanford may be the worst measure without adding other universities (how do we know there was not a selection bias?) And they don’t provide disaggregated data for Licenses, Patents, and Spin-Offs, which makes it even tougher to put into perspective.
Literature note: Vinig2015
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