Johannes Könemann, M.Sc.
Doctoral Student and Junior Research Fellow
Innovation and Entrepreneurship Research
+49 89 24246-567
johannes.koenemann(at)ip.mpg.de
Areas of Interest:
Behavioral and Experimental Economics, Industrial Organization, Innovation
Academic Résumé
Since 10/2024
Junior Research Fellow and Doctoral Candidate, Max Planck Institute for Innovation and Competition (Innovation and Entrepreneurship Research)
09/2022 – 01/2023
Exchange Semester, University of Zurich, Switzerland
10/2021 – 06/2024
Master of Science (M.Sc.) in Economics, Vienna University of Economics and Business, Austria
09/2019 – 01/2020
Exchange Semester, Uppsala University, Sweden
10/2017 – 01/2021
Bachelor of Science (B.Sc.) in Economics, University of Göttingen, Germany
Work Experience
03/2024 – 07/2024
Internship, Directorate-General for Economic and Financial Affairs, European Commission, Brussels
09/2023 – 02/2024
Tutor, Department of Economics, Vienna University of Economics and Business, Vienna
07/2023 – 09/2023
Internship, ifo Center for Public Finance and Political Economy, ifo Institute, Munich
02/2023 – 05/2023
Teaching and Research Assistant, Institute for Digital Ecosystems, Vienna University of Economics and Business, Vienna
07/2022 – 09/2022
Internship, Economic Consulting, Frontier Economics Limited, Berlin
03/2021 – 07/2021
Internship, Audit Attestation, KPMG AG, Munich
04/2020 – 09/2020
Tutor, Chair of Microeconomics, Göttingen University, Göttingen
Honors, Scholarships, Academic Prizes
2019/2020 and 2020/2021
Deutschlandstipendium
Publications
Conference papers
(2024). The Heart of Effort: Revealing Heart Rate Patterns in Real-Effort Tasks, in: Fred D. Davis et al. (
- Many laboratory experiments use real-effort tasks to increase the external validity of their findings. Real-effort tasks activate emotional reactions that are absent in stated-effort tasks. But there is little evidence whether and to which extent emotional reactions differ between participants, and how they affect effort provision. Since self-reported measures can be sensitive to the experimental context, we use heart rate measurements to investigate how participants feel during the task. We conducted a real-effort experiment with 84 participants and collected heart rate data with Polar H10 Heart Rate Sensors. We applied time series clustering on the heart rate data, focusing on shape-based distance (SBD) and k-shape clustering for analysis. The results demonstrate differences in heart rate patterns
among participant clusters, but not in effort provision. This research contributes to a better understanding of emotional reactions during real-effort tasks and offers a novel approach to studying these emotions using heart rate measurements. - https://publikationen.bibliothek.kit.edu/1000172245
- Event: NeuroIS Retreat, Wien, 2024-06-09