Universität Wien

040233 SE Bachelorseminar (inkl. Bachelorarbeit) (2024W)

8.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung

Moodle
Mi 08.01. 09:45-14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 24 Teilnehmer*innen
Sprache: Deutsch, Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Dienstag 08.10. 09:45 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Mittwoch 20.11. 09:45 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Montag 16.12. 15:00 - 18:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 17.12. 09:45 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Mittwoch 29.01. 09:45 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 30.01. 11:30 - 13:00 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

"The unknown future rolls toward us." (Sarah Connor, Terminator 2)

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

Art der Leistungskontrolle und erlaubte Hilfsmittel

1. Study Pre-Registration with deadline 24.11.2024 (peer-grading) (15 points)
2. Two peer-reviews on study-preregistrations with deadline 08.12.2024 (peer-grading) (20 points)
3. Concept Presentation during seminar block in December (5 points)
4. Final Science Slam presentation on 29.01.2025 (peer-grading) (10 points)
5. Final seminar paper with deadline 16.2.2025 (50 points)

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

Mindestanforderungen und Beurteilungsmaßstab

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

Prüfungsstoff

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

Literatur

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.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 23.09.2024 10:05