Prof. Dr. Paul Hünermund

Paul Hünermund

Scientific employee


Max-von-Laue-Straße 1
28359 Bremen
Building WIWI 2, Room F 2080




  • Innovation economics
  • Strategy
  • Organization science


Paul Hünermund is an Assistant Professor of Strategy and Innovation at Copenhagen Business School and scientific employee in the project Mod-Block-GDR at the University of Bremen. In his research, Dr. Hünermund studies how firms can leverage new technologies in machine learning and artificial intelligence for value creation and competitive advantage. His work explores the potential for biases in organizational decision-making and ways for managers to counter them.

To study the determinants of firm innovation activities and performance, his research builds on ideas from various disciplines, including economics, business strategy, game theory, and psychology. Furthermore, it employs a range of methods from econometrics, machine learning, and the field of causal inference. Dr. Hünermund’s work provides policymakers insights on how to optimally design public R&D support schemes, which he has communicated widely in consulting projects and keynote addresses to the European Commission, the German Federal Ministry of Research and Education, and the OECD. He co-founded, a platform for fostering knowledge exchange between industry and academia on topics related to causal data science.

His research has been published in the Journal of Management Studies, the Econometrics Journal, Research Policy, Journal of Product Innovation Management, International Journal of Industrial Organization, MIT Sloan Management Review, and Harvard Business Review, among others. He serves on the editorial board of the Journal of Causal Inference and the executive team of the Technology and Innovation Management (TIM) division at the Academy of Management. Dr. Hünermund pursued his studies in economics at the University of Mannheim, HEC Lausanne, and NYU Stern School of Business. He holds a Ph.D. in business economics from KU Leuven in Belgium. His contributions and commentary have been featured in renowned publications such as the Economist, the Wall Street Journal, Frankfurter Allgemeine Zeitung, Süddeutsche Zeitung, Politiken, and Neue Zürcher Zeitung. Additionally, he was honored as one of the “top 40 under 40” by Capital Magazine in 2021.


Academic education and degrees

2023 - Today

University of Bremen, Project „Obstacles to Modernization in the Economy and Science of the GDR” (Mod-Block-DDR)

2020 –Today

Copenhagen Business School,
Department of Strategy and Innovation (SI),
Assistant Professor (tenure track)

2017 – 2020

Maastricht University, School of Business and Economics, Department of Organisation, Strategy and Entrepreneurship (OSE), Assistant Professor (tenure track)

2013 – 2017

KU Leuven
Department of Management, Strategy and Innovation (MSI),
Ph.D. Student

2012 – 2017

Centre for European Economic Research (ZEW), Mannheim, Department of Economics of Innovation and Industrial Dynamics, Research Associate

2010 – 2012

M.Sc. Volkswirtschaftslehre, Universität Mannheim

2007 – 2010

B.Sc. Volkswirtschaftslehre, Universität Mannheim


11.2023 - 09.2025

Modernisierungsblockaden in Wirtschaft und Wissenschaft der DDR (Mod-Block-DDR)

Projektpartner: Friedrich-Schiller-Universität Jena, Europa-Universität Viadrina Frankfurt (Oder)

Gefördert von: Bundesministerium für Bildung und Forschung (BMBF)


Peer-reviewed publications


Grosz, M. P., Ayaita, A., Arslan, R. C., Buecker, S., Ebert, T., Hünermund, P., Müller, S. Rieger, S., Zapko-Willmes, A., Rohrer, J. M. (2023). Natural Experiments: Missed Opportunities for Causal Inference in Psychology. Advances in Methods and Practices in Psychological Science, forthcoming. (Scopus CiteScore: 26.8)


Bammens, Y., Hünermund, P. (2023). Ecological community logics, identifiable business ownership, and green innovation as a company response. Research Policy, 52(8): 104826. (VHB-JOURQUAL 3: A; AJG-2021: 4*)


Hünermund, P., Louw, B., Caspi, I. (2023). Double Machine Learning and Automated Confounder Selection: A Cautionary Tale. Journal of Causal Inference, 11: 20220078. (JIF: 1.4)


Hünermund, P., Bareinboim, E. (2023). Causal Inference and Data Fusion in Econometrics. The Econometrics Journal, forthcoming. (AJG-2021: 3)


Rohrer, J. M., Hünermund, P., Arslan, R. C., Elson, M. (2022). That's a lot to Process! Pitfalls of Popular Path Models. Advances in Methods and Practices in Psychological Science, 5(2): 1–14. (Scopus CiteScore: 26.8)


Bammens, Y., Hünermund, P., Andries, P. (2021). Pursuing Gains or Avoiding Losses: The Contingent Effect of Transgenerational Intentions on Innovation Investments. Journal of Management Studies, 59(6): 1493–1530. (VHB-JOURQUAL 3: A; AJG-2021: 4)


Hamstra, M. R. W., Schreurs, B., Jawahar, I. M., Laurijssen, L. M., Hünermund, P. (2021). Manager narcissism and employee silence: A socioanalytic theory perspective. Journal of Occupational and Organizational Psychology, 94(1): 29–54. (VHB-JOURQUAL 3: B; AJG-2021: 4)


Boeing, P., Hünermund, P. (2020). A global decline in research productivity? Evidence from China and Germany. Economics Letters, 197. (VHB-JOURQUAL 3: B; AJG-2021: 3)


Bammens, Y., Hünermund, P. (2020). Nonfinancial considerations in eco-innovation decisions: The role of family ownership and reputation concerns. Journal of Product Innovation Management, 37(5): 431–453. (VHB-JOURQUAL 3: A; AJG-2021: 4)


Andries, P., Hünermund, P. (2020). Firm-level effects of staged investments in innovation: The moderating role of resource availability. Research Policy, 49(7). (VHB-JOURQUAL 3: A; AJG-2021: 4*)


Czarnitzki, D., Hünermund, P., and Moshgbar, N. (2020). Public Procurement of Innovation: Evidence from a German Legislative Reform. International Journal of Industrial Organization, 71. (VHB-JOURQUAL 3: B; AJG-2021: 3)


Hünermund, P., and Czarnitzki, D. (2019). Estimating the Causal Effect of R&D Subsidies in a Pan-European Program. Research Policy, 48(1), 115–124. (VHB-JOURQUAL 3: A; AJG-2021: 4*)


Non peer-reviewed publications


Boeing, P., Hünermund, P. (2023). Is there a slowdown in research productivity? Evidence from China and Germany, in Artificial Intelligence in Science: Challenges, Opportunities and the Future of Research, OECD Publishing, Paris.


Bammens, Y., Hünermund, P. (2023). Using Federated Machine Learning to Overcome the AI Scale Disadvantage. MIT Sloan Management Review, 65(1), fall issue. (VHB-JOURQUAL 3: C; AJG-2021: 3)


Bammens, Y., Hünermund, P. (2021). How Midsize Companies Can Compete in AI. Harvard Business Review, September. (VHB-JOURQUAL 3: C; AJG-2021: 3)


Hünermund, P. (2021). Herausforderungen für die Innovationspolitik. In Frenzel, M., Machnig, M., Zenke, I. (Hg.). Post Coronomics – Neue Ideen für Markt, Staat und Unternehmen. Bonn, Germany: Dietz.


Boeing, P., and Hünermund, P. (2020). More R&D, Less Growth? Chinas Decreasing Research Productivity in International Comparison. ZEW Policy Brief Nr. 20-08, Mannheim.


Hünermund, P., Czarnitzki, D. (2019). Innovation Policy and Causality. ifo DICE Report 4 / 2019 (Winter): Innovation Policy, 3–6.


Hünermund, P. (2017). Do Most Companies Even Try to Innovate Anymore? Harvard Business Review, April. (VHB-JOURQUAL 3: C; AJG-2021: 3)


Hünermund, P., and Licht, G. Joint programming in European science and technology policy. 8 July 2016.


Hünermund, P., Schmidt-Dengler, P., and Takahashi Y. 2014. Entry and Shakeout in Dynamic Oligopoly. ZEW Discussion Paper No. 14-116.