Measuring Technological Novelty with Patent-based Indicators
Dennis Verhoeven, Research Foundation Flanders (FWO), KU Leuven?
Part 1: Measuring technological novelty with patent-based indicators. (Joint work with Reinhilde Veugelers and Jurriën Bakker)
This study provides a new, more comprehensive measurement of technological novelty. Integrating insights from the existing economics and management literature, we characterize inventions ex ante along two dimensions of technological novelty: Novelty in Recombination and Novelty in Knowledge Origins. For the latter dimension we distinguish between Novel Technological and Novel Scientific Origins. For each dimension we propose an operationalization using patent classification and citation information. Results indicate that the proposed measures for the different dimensions of technological novelty are correlated, but each conveys different information. We perform a series of analyses to assess the validity of the proposed measures and compare them with other indicators used in the literature. Moreover, an analysis of the technological impact of inventions identified as novel shows that technological novelty increases the variance of technological impact and the likelihood of being among the positive outliers with respect to impact. This holds particularly for those inventions that combine Novelty in Recombination with Novelty in Technological and Scientific Origins. Overall, the results support our indicator as ex ante measure of technological novelty with the potential to drive radical technological change.
Link to paper: https://www.dropbox.com/s/253c8bj93hnj66t/Research%20Policy%202016.pdf?dl=0
Part 2: Rational industrial policy: Standing on the shoulders of Giant Gnomes? (Joint work with Charlotte Guillard, Ralf Martin, Pierre Mohnen and Catherine Thomas)
The total economic value of an innovation is widely believed to exceed its privately appropriated value because of positive externalities arising from knowledge spillovers. A rational industrial policy for R&D addresses resulting market failure by targeting areas of innovative activity with relatively high potential for knowledge spillovers. Motivated by this rationale, we propose a method to quantify total economic returns to R&D support. To do so, we first introduce Patent Rank, a new measure for the value of knowledge spillovers. This new measure applies the logic of Google's PageRank algorithm to the network of patented innovations linked by citations. Next, we rely on a simple model of innovation to estimate the marginal total economic returns of subsidizing an area -- an indicator we call IStraX. Implementing our framework on a set of over 17 million innovations uncovers large heterogeneity across technological fields and countries in terms of the expected marginal returns to subsidies. As such, our results leave little hope for a `one-size-fits-all' industrial strategy and highlight the importance of accurately predicting knowledge spillovers on a fine-grained level of analysis.
Link to paper: https://www.dropbox.com/s/3rz7rmzpq0st2s7/RIPgnome.pdf?dl=0
Link to webinar: https://eu.bbcollab.com/guest/4fa9fc0c76994768a2ab084e3b027d89
About the speaker
Dennis Verhoeven is an FWO postdoctoral researcher at the department of Management, Strategy and Innovation (KU Leuven) and a research associate at the Centre for Economic Performance (LSE). During his PhD, he worked on the project ‘Radical Innovation’ (promoted by Reinhilde Veugelers), and was a visiting scholar at Duke University. Afterwards, he received a PDM scholarship from KU Leuven and worked for the ‘Chair for Belgian Business Champions’ (with Luc Sels and Bart Van Looy). Before starting his current postdoctoral fellowship, he worked as a research officer at the Centre for Economic Performance at LSE for the Horizon 2020 project ‘WATSON Innovation Analytics’ (promoted by Ralf Martin).
Broadly speaking, Dennis’ research interests lie in the area of economics of innovation and science. His dissertation focuses on measuring and analyzing technological novelty using patent-based indicators. Furthermore, it explores the relationship between the knowledge composition in teams and breakthrough innovation outcomes. His more recent work focuses on industrial policy for innovation, the link between scientific knowledge and innovation, and the gender gap in science and technology.
Venue: Online
Date: 16 June 2020
Time: 11:00 - 12:00 CET
