Since October 2024, Dominik Asam has been a Junior Research Fellow and doctoral candidate in the Economics Department of the Institute. He completed his award-winning master’s thesis at the Chair for Economics of Innovation at the Technical University of Munich under the supervision of Professor Hanna Hottenrott. He continues his research on this topic at the Institute in a joint project with David Heller, Assistant Professor at Politecnico di Milano and Affiliated Research Fellow at the Institute.
Asam and Heller provide novel insights into how technological change impacts firm-level productivity. They highlight the potential of new general-purpose technologies to fundamentally change the dynamics of entrepreneurial firms. Their study focuses on the impact of Generative AI (GenAI) on startup funding dynamics, finding that GenAI significantly increases startup productivity. This is evidenced by a 20% reduction in the average time to funding compared to startups not benefiting from the new technology.
The authors argue that valuable but non-exclusive technological innovations can serve as a source of competitive advantage when entrepreneurs strategically leverage them as complementary assets to their existing skill sets. The effects are particularly pronounced in startups led by founders with greater technological or managerial experience. This underscores the importance of complementary human resources in fully harnessing the value of Generative AI.
The special award from the Deutsche Bundesbank Regional Office in Bavaria recognizes outstanding theses from selected Bavarian universities in areas such as monetary policy, banking regulation, cash and non-cash payment systems, and financial stability. The award ceremony took place at the premises of the Deutsche Bundesbank in Munich and was presented by Reinhold Vollbracht, President of the Regional Office in Bavaria.
More at SSRN:
Asam, Dominik; Heller, David (2024). Generative AI and Firm-level Productivity: Evidence from Startup Funding Dynamics. Available at SSRN: https://ssrn.com/abstract=4877505