Strategy and innovation scholars have long emphasized the positive role of market demand in driving innovation within a technological domain. This study sheds light on an indirect negative spillover effect of  market demand on innovation: while increased downstream market demand within a technological domain generally drives increased innovation activities in that domain (i.e., the demand-relevant domain), it may also adversely affect the innovation of firms in adjacent domains. This occurs because the increase in innovation activities within the demand-relevant domain, driven by the downstream market demand, can intensify competition for skilled knowledge workers—a critical innovation resource whose supply is often inelastic in the short term. Empirically, I test these arguments by exploiting an unexpected environmental policy shock—the Zero Emission Vehicle (ZEV) mandate—which led to an exogenous increase in demand for electric vehicle (EV) technologies. Following the ZEV mandate, I find evidence of increased innovation activities in the EV domain by EV firms. However, firms in adjacent (non-EV) domains became 26% less innovative, particularly in their core technological areas, and 22% less likely to explore new technological areas. Importantly, this decline in innovation among these affected firms was driven by the loss of knowledge workers to EV firms. These effects were especially pronounced for affected firms that were more active in other growing technological domains and renewable energy domains.

Firms and policymakers are highly dependent on academic science for knowledge advancement to help overcome technological barriers and address pressing societal challenges, and they increasingly engage in shaping the research direction of high-quality academic scientists towards certain innovation domains. However, we know relatively little about how scientists respond to an increased demand for their expertise in an innovation domain. In this paper, I examine how scientists’ research productivity (which proxies their research ability) and intellectual distance from the demand shape their propensity to respond to the demand and the quality of their research outcomes in the domain. Empirically, I exploit an unanticipated environmental policy shock that led to increased demand for innovation in electric vehicle (EV) technologies. Empirical results suggest that more productive scientists (from both close and distant domains) are more likely to produce higher-quality EV research outcomes. Furthermore, EV research that includes productive coauthors from distant domains are more likely to be of higher quality and to be utilized in future technological innovations (i.e., patents). However, I also find that as scientists’ distance from the EV domain increases, more productive scientists progressively have reduced incentive to engage with EV research, relative to less productive scientists. Specifically, in domains intellectually closer to EV research, more productive close scientists are more likely to engage with EV research than less productive close scientists. By contrast, in domains intellectually more distant from EV research, less productive distant scientists are relatively more likely to engage with EV research than more productive distant scientists.

Large corporate labs play an important role in innovation. Recently, there has been a trend toward universities producing scientific research and then corporate labs developing this research into practical applications. This division of scientific research labor can have negative consequences for the development of general purpose technologies and other enabling technologies. These technologies rely on a positive feedback loop of innovation, from seeding to complementary trajectories and back, in order to generate substantial productivity gains for companies and for the economy overall. A push against the increasing division of scientific research labor may catalyze the feedback loop. We explore this possibility in the context of the development of quantum computers. After a change in companies’ incentives to engage in scientific research, following a surprise announcement about the near-term commercial potential of quantum computing, we document a rise in company academic publications and patents in quantum computing hardware. Soon after, we document a rise in academic publications and patents in the complementary software trajectory. We also find suggestive evidence of a feedback loop between the hardware and the software trajectories. We interpret these results to suggest complementarities between company and university scientific research in the context of a newly emerging enabling technology.

Understanding factors affecting the direction of innovation is a central aim of research in the economics of innovation. Progress on this topic has been inhibited by difficulties in measuring distance and movement in knowledge space. We describe a methodology that infers the mapping of the knowledge landscape based on text documents. The approach is based on an unassisted machine learning technique, Hierarchical Dirichlet Process (HDP), which flexibly identifies patterns in text corpora. The resulting mapping of the knowledge landscape enables calculations of distance and movement, measures that are valuable in several contexts for research in innovation. We benchmark and demonstrate the benefits of this approach in the context of 44 years of USPTO data.

Using panel data on 251,511 patent inventors matched with voter registration records containing partisan affiliation, we provide the first large-scale look into the partisanship of American inventors. We document that the modal inventor is Republican and that the partisan composition of inventors has changed in ways that are not reflective of partisan affiliation trends amongst the broader population. We then show that the partisan affiliation of inventors is associated with technological invention related to guns and climate change, two issue areas associated with partisan divide. These findings suggest that inventor partisanship may have implications for the direction of inventive activity.