Universität Wien

040238 SE Bachelor Seminar (incl. Bachelor´s Paper) (2025S)

8.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle
We 30.04. 09:45-11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 24 participants
Language: German, English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 19.03. 11:30 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 19.03. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 09.04. 11:30 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 09.04. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 30.04. 11:30 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 30.04. 13:15 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 30.04. 15:00 - 16:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 19.05. 09:45 - 11:15 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 19.05. 11:30 - 13:00 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 19.05. 13:15 - 14:45 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 17.06. 09:45 - 11:15 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 17.06. 11:30 - 13:00 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 18.06. 11:30 - 13:00 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 18.06. 13:15 - 14:45 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock

Information

Aims, contents and method of the course

In recent years, the advent of artificial intelligence (AI) has brought about a paradigm shift in organizational leadership. AI has emerged as a transformative force in the business landscape, granting organizations the power to revolutionize processes and ramp up productivity (Di Vaio et al., 2020). However, while the implementation of AI like chatbots or generative AI have been extensively investigated in the contexts of manufacturing (Kim et al., 2022) and marketing (Chintalapati et al., 2022), little research exists on the implications of introducing AI tools in leadership role (Song & Ford, 2022). Therefore, this seminar takes up the topic by asking whether chatbots and generative AI can facilitate leadership processes and even replace organizational leaders. To do so, we investigate

In this seminar, students will write a (pre-)scientific paper investigating the contingencies of as well as perceptions of both, followers and leaders towards AI in leadership. The goal is to identify enablers and hindrances using experimental and empirical research. Based on the work, students should identify strategies that should be embraced by individuals, educational institutions, organizations and policy makers to enhance organizational leadership.

The successful completion of the VO Introduction to Scientific Work as well as the VO and UE Statistics 1 constitutes a pre-requisite for attending this course. In addition, successful completion of the elective module VO and UE Statistics 2 is highly recommended because we will work with the programming language R and the statistics software RStudio in this seminar.

This seminar provides students with skills and knowledge on how to conduct a (pre-)scientific research project. More specifically, students will further their insights into the following topics through input presentations at the kick-off meeting, the provision of learning videos via Moodle and literature:
• Scientific literature review
• Identifying relevant theories
• Study pre-registration
• Data collection & analysis
• Scientific presenting
• Academic paper writing
• Peer reviewing

Assessment and permitted materials

1. Study Pre-Registration with deadline 13.04.2025 (peer-grading) (15 points)
2. Two peer-reviews on study-preregistrations with deadline 24.04.2025 (peer-grading) (20 points)
3. Concept Presentation on 30.04.2025 (5 points)
4. Final Science Slam presentation on 17.06.2025 (peer-grading) (10 points)
5. Final seminar paper with deadline 6.7.2025 (50 points)

All supporting tools, literature references, etc. must be cited. All submissions handed in on Moodle will be checked for plagiarism with TurnItIn and AI writing using an AI Content Detector. Accepting the usage of these tools constitutes a pre-requisite for registering for this course.

Minimum requirements and assessment criteria

Passing grades can only be achieved by students not missing more than 10% of the lectures.

To pass the course, students must achieve at least half of the points available in the seminar paper as well as in the course overall.

Passing grades are distributed accordingly based on overall course points:

50 to < 62.5 points: 4
62.5 to < 75 points: 3
75 to < 87.5 points: 2
87.5 points or better: 1

Examination topics

Input presentations during lectures
All materials distributed via Moodle
All literature readings

Reading list

Ebster, C. & Stalzer, L. (2017). Wissenschaftliches Arbeiten für Wirtschafts- und Sozialwissenschaftler, 5. Aufl., Wien. ISBN: 978-3-8252-4684-6 (erhältlich im Facultas Shop)

Sheppard, V. (2020). Research Methods for the Social Sciences: An Introduction. Victoria: BCcampus.

Sreejesh, S.; Mohapatra, S. & Anusree, M. R. (2014). Business Research Methods: An Applied Orientation. New York: Springer.

Wason, K. D.; Polonsky, M. J. & Hyman, M. R. (2002). Designing vignette studies in marketing. Australasian Marketing Journal, 10(3), 41-58.

Zamora-Saiz A.; Gonzalez, C. Q.; Hurtado Gil, L. & Ruiz, D. M. (2020). An Introduction to Data Analysis in R. New York: Springer.

Association in the course directory

Last modified: Fr 14.03.2025 15:25