*In all papers, all authors contributed equally. Authors listed in alphabetical, reverse alphabetical or random order.
Market Demand, Competition for Knowledge Workers, and Impact on Invention: Evidence from Electric Vehicle Technologies
Jino Lu
Minor revision at Organization Science
Best Conference Paper in Innovation and Entrepreneurship, Industry Studies Association Annual Conference, 2024
Best Conference Paper Finalist, Strategic Management Society Annual Conference, 2023
Best Conference PhD Paper, Strategic Management Society Annual Conference, 2023
Knowledge and Innovation Interest Group Best Paper Award, Strategic Management Society Annual Conference, 2023
Will Mitchell Dissertation Research Grant, Strategic Management Society, 2023
Greif Entrepreneurship PhD Research Award, USC Lloyd Greif Center for Entrepreneurial Studies, 2023
Dissertation Completion Grant, USC Marshall School of Business, 2023
Abstract
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 technological progress: whereas increased downstream market demand within a domain generally drives increased technological progress in that domain (i.e., the demand-relevant domain), it may also adversely affect the technological progress of firms in adjacent domains. This occurs because the increased technological progress 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 inventive activities in the EV domain by EV firms. However, firms in adjacent (non-EV) domains were more likely to lose knowledge workers to EV firms following the ZEV mandate. Consequently, these affected firms produced 22% fewer inventions, particularly in their core technological areas, and became 19% less likely to explore new technological areas. Notably, affected firms in growing technological domains, such as renewable energy, and smaller, younger firms were more adversely (or at least equally) impacted.
Demand for Research, Scientific Response, and Impact on Research Outcomes: The Interrelated Roles of Intellectual Distance and Productivity
Jino Lu
Revise & Resubmit at Organization Science
Best Conference PhD Paper, Strategic Management Society Annual Conference, 2022
The Bent Dalum Best PhD Paper Award, DRUID Academy Conference, 2023
Abstract
Policymakers and firms have become increasingly dependent on academic research for upstream scientific progress, especially in domains where technical challenges in downstream invention generate demand for additional research. This study examines which academic scientists produce research in a domain when demand for upstream scientific research in that domain increases. In particular, I examine how scientists’ propensity to produce research in that domain varies by their research productivity and intellectual distance from the domain, and how their response patterns shape the direction of research within that domain. Empirically, I exploit an unexpected environmental policy shock—the Zero Emission Vehicle (ZEV) mandate—which led to an exogenous increase in demand for upstream scientific research related to electric vehicle (EV) technologies. Following the ZEV mandate, there was an increase in the number of scientists producing EV research. However, I find that as scientists’ intellectual distance from the EV domain increased, more-productive scientists became disproportionately less likely to produce EV research than less-productive scientists. Notably, when more-productive scientists from intellectually more distant domains chose to produce EV research, they generated more novel and more impactful EV research outcomes than other scientists, including more-productive scientists from closer domains. These findings suggest a potential asymmetry in how academic scientists respond to increased demand for upstream scientific research in a domain: while more-productive scientists from intellectually more distant domains have significant potential to contribute novel and impactful research outcomes in that domain, they tend to be underrepresented among those who actually produce research in the domain.
Company and University Innovation during an Industry Incubation Phase: Evidence from Quantum Computing
Avi Goldfarb, Jino Lu, and Florenta Teodoridis
Revise & Resubmit at Management Science
Abstract
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.
Mapping the Knowledge Space: Exploiting Unassisted Machine Learning Tools
Florenta Teodoridis, Jino Lu, and Jeffrey L. Furman
Abstract
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.
Fehder, D., Teodoridis, F., Raffiee, J., & Lu, J. 2024. The partisanship of American inventors. Research Policy. 53(7): 105034
Abstract
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.