Seminar  |  12.04.2023 | 15:00  –  16:15

Innovation & Entrepreneurship Seminar: What Share of Patents Is Commercialized?

John P. Walsh (Georgia Tech)

Raum 313

Firms apply for patents for a variety of reasons. In addition to trying to prevent others from copying a commercialized patented invention, firms also patent one technology to support the commercialization of their other innovations (which we call “pre-emptive patents”). At the same time, many patent applications fail to yield commercialized products. A variety of policy debates revolve around the relative rates of these different uses of patents.  In particular, there is a concern that a large number of patents are not commercialized (with a common folk statistic stating that 10% or fewer are commercialized), raising concerns of over-patenting, with possible adverse effects on the innovation system. However, it has been difficult to get systematic evidence on the relative incidences of commercialized versus pre-emptive or failed patents. This paper applies advanced natural language processing (NLP) and machine learning (ML) methods to US patent documents to estimate the rates of patent uses of various types, over time at scale. We first use a survey of US inventors on the commercialization and other outcomes of their patents as independently labeled data for training our ML models. Using a combination of context embedding codings of the patent text (based on BERT) and bibliometric indicators from the patent documents, we develop a random forest model predicting different outcomes for patented inventions. We find that adding BERT coding of patents’ text contents offers new information beyond commonly used numeric and categorical variables reflecting patent characteristics (technology class, number of claims, patent class span, etc.) or token-based text analytics indicators, highlighting the benefits of adding context embedding NLP when categorizing patents. We check the validity of the trained model using external data on Virtual Patent Marking, and show that our model predicts high commercialization rates among patents that are indeed associated with commercialized products. We apply this trained model to the universe of all granted US patents, 1981-2015 to estimate the probabilities of various uses of the patents in this population. These estimates of usage probabilities are publicly available for other researchers to use in follow-on studies. Among US granted patents 1981-2015, the mean probability of commercialization is .59, and the mean probability of pre-emptive use is .19. Finally, we show how these probabilities vary by year, patent class, firm size, and government interest. The paper makes several contributions to understanding the uses of patents, as well as how to use ML to analyze patent data. In particular, we show that estimated rates of commercialized patents are substantially higher than is often asserted in policy discussion.

Ansprechpartnerin: Elisabeth Hofmeister

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Workshop  |  13.04.2023, 11:00  –  14.04.2023, 16:30

16th Workshop on the Organisation, Economics and Policy of Scientific Research

Max-Planck-Institut für Innovation und Wettbewerb

Das Max-Planck-Institut für Innovation und Wettbewerb und die Technische Universität München organisieren den jährlichen Workshop “The Organisation, Economics and Policy of Scientific Research”.

Die Teilnahme an der Veranstaltung ist offen und kostenlos: Bitte senden Sie eine E-Mail an michael.rose(at)

Zum Programm

Mehr Informationen auf der Workshop-Webseite

Seminar  |  19.04.2023 | 15:00  –  16:15

Innovation & Entrepreneurship Seminar: How Scientific Organizations Adapt to Novel Methodological Advances – The Impact of AlphaFold V1

Gabriel Cavalli (University of Toronto)

Online-Veranstaltung, auf Einladung, siehe Seminarseite

This paper analyzes the unexpected success of AlphaFold V1, an AI-based software program representing a publicly available and novel methodological advance within the “protein folding” (PF) subfield of computational biology. As a novel tool that represented a significant advance, AlphaFold V1 influenced the size and the expertise composition of academic research labs already producing similar software in the PF subfield. Specifically, AlphaFold V1 caused the principal investigators of established labs to reconsider the size, and the depth and breadth of expertise necessary to capitalize on the advance; and even to decide whether their labs should continue work in the PF subfield altogether. Results show that impacted labs adapted to the new methodological advance by becoming larger and broader in expertise. This study contributes findings on: (i) the mechanisms of new opportunity and increased competition that shape lab composition; (ii) the complexity of science at the frontier of human expertise and artificial intelligence; and (iii) the role of companies in the collective effort to produce scientific knowledge. The results carry implications for further research on the integration of disciplinary insights, the scaled computational capabilities enabled by artificial intelligence, and the organization of science itself.

Ansprechpartner: Michael E. Rose

Seminar  |  26.04.2023 | 15:00  –  16:15

Innovation and Entrepreneurship Seminar: The Lost Ester Boserups – The Impact of Parenthood on Academic Careers

Anne Sophie Lassen (CBS)

Raum 313

Women continue to be underrepresented in the field of economics, especially among permanent faculty. Using 40 years of Danish administrative data combined with bibliometric data on publications from the Scopus database, we study the impact of children on women’s probability of successful academic careers. Our event study estimates show that parenthood reduces women’s likelihood of staying in academia by 10 percent relative to men, and the gap appears to be permanent. We further document a gender gap in the likelihood of getting tenure in the three years following parenthood, conditional on staying in academia, while the gender gap in publications is insignificant.

Ansprechpartnerin: Marina Chugunova

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Seminar  |  10.05.2023 | 15:00  –  16:15

Preview: Innovation & Entrepreneurship Seminar mit Reddi Rayalu Kotha

Reddi Rayalu Kotha (Singapore Management University)

auf Einladung, siehe Seminarseite

Abstract folgt.

Ansprechperson: Marina Chugunova

Seminar  |  01.06.2023 | 15:00  –  17:00

TIME Kolloquium

(auf Einladung)

Kaulbachstraße 45, ISTO (LMU)

Seminar  |  07.06.2023 | 15:00  –  16:15

Preview: Innovation & Entrepreneurship Seminar mit Erin Hengel

Erin Hengel (London School of Economics)

Online-Veranstaltung, auf Einladung, siehe Seminarseite

Abstract folgt.

Ansprechpartnerin: Svenja Friess

Seminar  |  14.06.2023 | 15:00  –  16:15

Preview: Innovation & Entrepreneurship Seminar mit Maximilian Todtenhaupt

Maximilian Todtenhaupt (Leibnitz Universität Hannover / NHH)

Raum 313

Abstract folgt.

Seminar  |  19.06.2023 | 16:30  –  17:45

Preview: Innovation & Entrepreneurship Seminar mit Luke Rhee

Luke Rhee (UC Irvine)

Online-Veranstaltung, auf Einladung, siehe Seminarseite

Abstract folgt.

Ansprechpartner: Michael Rose

Munich Summer Institute (MSI)
Tagung  |  24.06.2023, 09:00  –  26.06.2023, 18:00

Munich Summer Institute 2023

Bayerische Akademie der Wissenschaften

Munich Summer Institute (MSI)

Das Munich Summer Institute (MSI) wird veranstaltet vom Center for Law & Economics der ETH Zürich, dem Lehrstuhl für Technologie- und Innovationsmanagement der TUM, dem Lehrstuhl für Innovationsökonomie der TUM, dem Institut für Strategie, Technologie und Organisation der LMU München und dem Max-Planck-Institut für Innovation und Wettbewerb.

Zum Call for Papers

Weitere Informationen auf der Webseite des MSI