Knowledge that Transforms

False investigators are researchers who have been listed on grant proposals as part of a research team even though there is no expectation that they will contribute to the research effort. Their use seems to be widespread even though their inclusion raises legal and ethical questions. Using data collected from the top 200 universities listed on U.S. News and World Report (2015), this manuscript investigates whether the use of false investigators impacts the distribution of research money and if so, by how much? Our analysis suggests they do, grants with false investigators receive more money, and while the size of this return varies with grant size, we find an average increase of about 70%. We also investigate how this influence is manifested; whether the increased funding is because false investigators apply for more grants, or if the presence of a false investigator increases the amount of funding received per proposal. We close with a discussion of policy issues and questions about research funding that remain unanswered.

"Mission-oriented" public research organizations invest in R&D to improve decision-making around complex policy problems from climate change to asteroid impacts, thus producing public value. However, the estimation of benefits produced by such R&D projects is notoriously difficult to predict and measure - a challenge that is magnified for global catastrophic risks (GCRs). GCRs are highly uncertain risks that may pose enormous negative consequences for humanity. This article explores how public research organizations systematically reduce key uncertainties associated with GCRs. Building off of recent literature highlighting the organizational and political factors that influence R&D priority-setting at public research organizations, this article develops an analytical framework for explaining R&D priority-setting outcomes that integrates the key stages of decision analysis with organizational and political dynamics identified in the literature. This framework is then illustrated with a case study of the NASA Planetary Defense Coordination Office, which addresses the GCR of near-Earth object (asteroid and comet) impacts. The case study reveals how organizational and political factors interact with every stage in the R&D priority-setting process - from initial problem definition to project selection. Lastly, the article discusses the extent to which the case study can inform R&D priority-setting at other public organizations, particularly those addressing GCRs.

We investigate country-level determinants of Official Development Assistance (ODA) in health R&D with a focus on levels and types of human suffering as well as levels and types of medical absorptive capacity. Using latest data from a range of sources and various tests on large numbers of countries in receipt of health R&D ODA, we find support for the central assertions that human burden has a direct positive impact on receipt of health R&D ODA and that medical absorptive capacity in the recipient country moderates this relationship. The relationship between human burden and health R&D ODA receipt does not hold for countries low in medical absorptive capacity. Additional analysis reveals: (1) medical absorptive capacity that involves regular patient contact has the strongest moderating effect on the burden – funding relationship, (2) receipt of health R&D ODA under low levels of medical absorptive capacity explained not by human burden but by small country bias, and (3) the importance of nurses to health R&D ODA in countries with high levels of human suffering and health R&D ODA but voids of doctors and clinical trials.

How do you measure the value of a commodity that transacts at a price of zero from an economic standpoint? This study examines the potential for and extent of omission and misattribution in standard approaches to economic accounting with regards to open source software, an unpriced commodity in the digital economy. The study is the first to follow usage and upgrading of unpriced software over a long period of time. It finds evidence that software updates mislead analyses of sources of firm productivity and identifies several mechanisms that create issues for mismeasurement. To illustrate these mechanisms, this study closely examines one asset that plays a critical role in the digital economic activity, web server software. We analyze the largest dataset ever compiled on web server use in the United States and link it to disaggregated information on over 200,000 medium to large organizations in the United States between 2001 and 2018. In our sample, we find that the omission of economic value created by web server software is substantial and that this omission indicates there is over $4.5 billion dollars of mismeasurement of server software across organizations in the United States. This mismeasurement varies by organization age, geography, industry and size. We also find that dynamic behavior, such as improvements of server technology and entry of new products, further exacerbates economic mismeasurement.

To navigate the uncertainty inherent in science driven innovation, academic science teams must often undertake search through engagement with external actors. While both broad and narrow external engagement are beneficial to team search during innovation, it remains unclear how science teams coordinate and utilise engagement across time. To address this issue, we tracked the search activity of a publicly funded medical technology team in New Zealand over five and a half years. Our inductive analysis leads to a grounded theory process model showing how academic science teams manage their search activities during innovation across three stages of external engagement: devising and coordinating, assimilating, and distilling. Our study makes three contributions. First, we show that science team search progresses from broad engagement with clinicians, patients, and industry to narrow and stronger engagement between a select set of within team and external actors from these communities at later stages of the innovation process. Second, our research shows how science teams renew their search activities during innovation. As engagements around original project objectives are distilled to fewer and stronger engagements, other team resources are released and redeployed to pursue more exploratory avenues of research in tandem, thereby re-instating broader and more distant search within the team's innovation activities. Third, we introduce to the literature and detail two transition points (i.e., brokering and control) through which science team search is distilled. We discuss the implications of our findings for research policy and practice.