I study how firms, scientists, and institutions create, protect,
and commercialize new technologies.
I am particularly interested in
intellectual property, R&D governance, patent systems, and the organizational
choices that shape learning and innovation. Increasingly, my work also uses
AI, machine learning, and computational chemistry to study technological
trajectories directly at the level of scientific and molecular artifacts.
Results of my research have been publised in top management journals and beyond including
Academy of Management Journal, Harvard Business Review, Management Science,
Strategic Management Journal, Review of Economics and Statistics and
Research Policy. Major media outlets such as the Financial Times, Forbes,
or the Wall Street Journal covered it.
SUSTECH investigates how technological trajectories emerge and why some
alternatives are selected over others. The project focuses on chemical
inventions and develops new ways to study technologies through their
molecular structure, rather than only through patents, classifications,
citations, or text.
The project combines computational chemistry, machine learning, and the
economics of innovation to derive information about the properties of
inventions directly from their underlying structure. This makes it possible
to compare technological alternatives in terms of functional performance,
environmental impact, and potential risks at earlier stages of development.
It has been awarded a prestigious ERC Synergy grant from European Research Council
amounting to a funding volume of 10 Mio. EUR over six to be split amongst the four co-PIs.
Visit the SUSTECH project page →
Ongoing Projects
Cross-functional feedback and patent examination performance
With Tetsuo Wada (Gakushuin University, Tokyo), this project studies the Japan Patent Office’s personnel
rotation system, in which mid-career patent examiners temporarily serve as
administrative judges in the Trial and Appeal Department before returning
to examination. The project asks whether moving professionals from
production into review roles creates feedback that improves later
performance.
Using examiner-level panel data and an event-study difference-in-differences
design, the paper finds that post-rotation examiners increase productivity
while lowering first-action grant rates, consistent with more selective and
review-informed examination behavior.
The hidden costs of collaborating in imitation-oriented R&D
With Xu Li (London School of Economics), this project examines whether R&D alliances help or hinder
firms’ transition from imitation to original innovation. The empirical
setting is the Chinese pharmaceutical industry, where firms reverse-engineered
foreign drugs either internally or through alliances with firms, universities,
and research institutes.
The paper argues that alliances can improve short-run efficiency by pooling
complementary expertise, but may reduce long-run learning when tasks are
partitioned across partners. The findings suggest that imitation experience
supports later new-to-the-world innovation, but that this benefit is weaker
when imitation is accumulated through alliances rather than internally.
Bureaucracy Index Germany
This project develops a quantitative index of bureaucracy in Germany based
on the volume of applicable federal legislation. The index measures the
development of German federal law over time and uses the total volume of
legal text as an indicator of regulatory density.
Bureaucracy Index Germany →
