Even if alt causes to lack of commercialization, multiple indicators prove poor performance by universities

[John E., III, 2013 Volume 38, Journal Technology Transfer, “Redeploying Bayh-Dole: beyond Merely doing good to optimizing the potential in results of taxpayer-funded research”, Springer - DOI 10.1007/s10961-011-9231-x, accessed on 7-16-2024, GDI-ALG]

Conclusions that university technology transfer efforts are not optimizing potential have been attacked as flawed and misguided because there is no supporting data. In other words, because there are no definitive statements of potential, there can be no way to determine whether that potential is being achieved or not. It therefore follows, the argument continues, that criticisms grounded in pursuing potential lack merit and the status quo should be complacently maintained. Stated differently, the attack argues that barriers to doing better and impediments to advancing economic growth and human welfare should be sustained because an ideal or even improved state cannot be objectively declared or realized with certainty.

Admittedly, there is no unequivocal, absolute data such as that which such critics seek, but there are analyses that can be done of the financial returns on funds invested in research that would show such returns as deficient (Litan and Cook-Deegan 2011; Tyler 2009). For instance, Litan and Cook-Deegan found a range of 0.3–4.3% as the average annual percentage return on expenditures for the top ten recipients of cumulative licensing income between 1996 and 2008. Four of those ten had an average annual return of 0.5% or less; five had returns greater than 1%; and only two had returns higher than 2% (2011).

Such an analysis, however, over-emphasizes monetary returns and neglects other important contributions (Litan and Cook-Deegan 2011; Tyler 2009). But it seems ironic and paradoxical that one of the standards of measure most emphasized by university leaders—revenue—is argued as inadequate or irrelevant when presented as a counter point to encourage the need for improvement.

The absence of an ideal or perfect foil against which to measure performance, however, is not a prerequisite for evaluating performance and making suggestions for improvement. For instance, there are other indicators of suboptimal performance, including the extent to which researchers use ‘‘backdoor’’ approaches to avoid technology transfer offices (Litan and Cook-Deegan 2011; Audretsch and Aldridge 2010; Thursby et al. 2009) and research productivity (Litan and Cook-Deegan 2011). Moreover, it is possible to analyze systems, processes, and practices and identify obvious barriers to the ultimate goals that if removed are likely to enable progress toward those goals (Tyler 2009; see Litan and Cook-Deegan 2011). It also may be inferred from continued tolerance of those barriers, when assessed in a broader context, whether university leaders focus on Bayh-Dole’s tactics or its more important policy purposes with the attendant consequences.

Although there is context to be gained from appreciating that industry and government also can impede efforts to maximize the usefulness of the results of taxpayer-funded research, it does not follow that interference by industry and government neutralizes criticisms of university efforts. Similarly, certain critiques of university policies, practices, and behaviors as reflections of approaches to federal policy do not suffer because of a lack of data against which to compare for optimal implementation.