Department of Digitalization

External Lecturer

Daniel Hain
Presentation and academic fields

As professor at the AAU Business School, I lead the Data Science research at the AI:Growth lab, and the Programme Director of the M.Sc. program in Business Data Science. As part of the AI:DK project, I coordinates and leads AI proof-of-concept projects within industry. My team also develops enterprise and policy software solutions for IP search and technology mapping.

Professional and/or academic experience

My research is dedicated to the development and application of data-driven methods to map, understand, and predict technological change, and its causes and consequences for socioeconomic systems on various levels of aggregation. My current contextual focus is the dynamics of AI research & industry, and the development of neurotechnologies. Outcomes are featured in leading academic journals such as "Research Policy" and "Technological Forecasting and Social Change", but also attracted attention and funding from the industry, and lead to price-winning applications.

Pedagogical experience/method skills/supervision

I am actively engaged in initiatives to educate (social science) students & researchers, professionals, and policymakers in understanding, evaluating, and applying modern Data Science and Artificial Intelligence methods for data-driven decision making. I coordinate and teach programmes and courses related to data science applications internationally, including AAU, Copenhagen Business School, the United Nations University Maastricht, Strasbourg University, and the University of the Chinese Academy of Science. I also supervise data driven projects and theses on Bachelor, Master, and PhD level.


Other Teaching Activities

Selected Publications:

  •  Hain, D.S., Jurowetzki, R, Lee, S. & Zhou, Y. (forthcomming). Machine Learning and AI for Science, Technology, and (Eco-)System Mapping and Forecasting: Introduction to the Special Issue. Scientometrics
  • Hain, D. S., & Jurowetzki, R. (2020). The promises of Machine Learning and Big Data in entrepreneurship research. In Handbook of quantitative research methods in entrepreneurship. Edward Elgar Publishing.
  • Wang, D., Hain, D. S., Larimo, J., & Dao, L. T. (2020). Cultural differences and synergy realization in cross-border acquisitions: The moderating effect of acquisition process. International Business Review, 101675.
  • Martins, R. M., Park, E. K., Hain, D. S., & Jurowetzki, R. (2020). Mapping the Entrepreneurial Ecosystem for Technology Start-ups in Developing Economies. An Empirical Analysis of Twitter Networks between Start-ups and Support Organizations of Nairobi’s Digital Economy. In Handbook of Entrepreneurship, Technology Commercialisation and Innovation Policy in Africa.
  • Rakas, M., & Hain, D. S. (2019). The state of innovation system research: What happens beneath the surface?. Research Policy48(9), 103787.
  • Christensen, J. L., Hain, D. S., & Nogueira, L. A. (2019). Joining forces: collaboration patterns and performance of renewable energy innovators. Small Business Economics52(4), 793-814.
  • Hain, D. S., & Christensen, J. L. (2019). Capital market penalties to radical and incremental innovation. European Journal of Innovation Management.
  • Hain, D., Buchmann, T., Kudic, M., & Müller, M. (2018). Endogenous dynamics of innovation networks in the German automotive industry: analysing structural network evolution using a stochastic actor-oriented approach. International Journal of Computational Economics and Econometrics8(3-4), 325-344.
  • Hain, D. S., & Jurowetzki, R. (2018). Local competence building and international venture capital in low-income countries. Journal of Small Business and Enterprise Development.
  • Christensen, Jesper Lindgaard, and Daniel S. Hain. "Knowing where to go: The knowledge foundation for investments in renewable energy." Energy Research & Social Science 25 (2017): 124-133.
  • Hain, D. S., & Jurowetzki, R. (2017). Incremental by Design? On the Role of Incumbents in Technology Niches. In Foundations of Economic Change (pp. 299-332). Springer, Cham.
  • Hain, D., Johan, S., & Wang, D. (2016). Determinants of cross-border venture capital investments in emerging and developed economies: The effects of relational and institutional trust. Journal of Business Ethics138(4), 743-764.
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