Megaprojects, Digital Platforms, and Productivity: Evidence from the Human Brain Project
Presenter: Ann-Christin Kreyer (MPI)
Discussant: Elisa Gerten (ISTO)
How to build institutions to facilitate large-scale, long-term life science projects? This paper studies the impact of the Human Brain Project (HBP), a 10-year (2013-2023) flagship project funded by the European Union, which offers a valuable setting for institutions that provide long-term infrastructure and grant support to neuroscience, computing, and brain-related medicine. We construct new data that track the individuals involved in the HBP, the timing of active engagement, and research output (e.g., publications). We exploit plausibly exogenous variation based on the phase-relevant resource allocation and individual engagement. We use current methods in the difference-in-difference (DiD) with two-way fixed effects, combined with natural language processing tools (esp. topic classification) to capture the evolution in research topics: fundamental neuroscience, neurotech, AI-robotics, and patient care. We find that the HBP has gained attraction over time, with more individuals actively participating from more geographically diverse bases, particularly junior faculties and graduate students. We find that participation in the HBP leads to increased individual productivity in publications per year, an expanded coauthor network, more citations, and a higher likelihood of publishing in a top neuroscience journal. All topic areas share the increased research productivity and impact, especially in the neurotech topic areas that combine neuroscience and CS/AI. These results are particularly driven by junior scholars (junior faculties and graduate students). The overall patterns are qualitatively similar for the subsample containing female scholars, despite smaller magnitudes and less precision. Scholars based in Germany, Italy, and Belgium demonstrated more pronounced increases in publications per author year for neuroscience and AI researchers. This paper has broad policy implications with new evidence that upstream digital collaborative institution design can help facilitate high-impact interdisciplinary neuroscience research, which is a critical input in discovering new and better treatments for brain diseases.
Suing Upstream or Downstream? A Value Chain Perspective on Defendant Selection in Patent Infringement Suits
Presenter: Adrian Goettfried (TUM)
Discussant: Elisabeth Hofmeister (MPI)
Patent infringement suits may target various parties in the value chain, from the original implementer who translated the patented invention into a technical artifact downward to a commercial user of the final product. We analyze the plaintiff’s selection of “litigation level”, i.e., the level in the value chain on which the defendant is active. We distinguish between “direct litigation”, where the defendant is the original implementer of the patent; and “indirect litigation”, where the defendant is downstream from the original implementer. Drawing on anchoring and transaction cost theory, we hypothesize which factors render bifurcated patent infringement suits more likely. We present empirical findings from a study of 247 patent infringement suits filed at US district courts between 2010 and 2016. 38% of the analyzed patent infringement suits are indirect, with a particularly high prevalence in retail trade (78%) and services (58%; e.g., software or computer services). Indirect suits are relatively rare in manufacturing industries (25%), with electronics being the only exception (51%). In multivariate analysis, we find indirect patent infringement suits to be associated with complex technologies, open standards covered by standard-essential patents, and product patents, supporting three of our hypotheses. We contribute theoretically to research on value capture by suggesting antecedents of direct and indirect patent infringement suits. We discuss policy implications arising from the relative efficiency of the two modes and identify the need for managers to take an end-to-end perspective on IP risks in the value chain.