Universität Wien

040228 UE Experimental Methods I: Agent Based Modelling in Organisations (MA) (2023S)

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

An/Abmeldung

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

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Mittwoch 08.03. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 15.03. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 22.03. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 29.03. 08:00 - 11:20 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 19.04. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 26.04. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 03.05. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Mittwoch 14.06. 08:00 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Agent Based Modelling, and Computational Methods in general, can provide valuable insights into the functioning of organisations. In academic research, simulations have long been used as a complementary tool besides traditional empirical work and laboratory experiments to produce propositions for empirical validation, model real-world scenarios and generate artificial datasets.

This class is an introductory course to modelling techniques in the context of organizational studies and should serve as a basis for the corresponding follow-up course. Whereas this second class will be focused on actual implementation of simulations, the first course will lay out the foundations for this by focusing on understanding the main ingredients needed in computational modelling, developing ideas on how to get from a research question to an actual model (mainly on the basis of pseudocode) and providing an introduction to the programming language Python which will be used for implementation later on.

Students will learn when computational models can be used, how they can be usefully employed and what the main advantages and limitations of this method are. Furthermore, participants will be familiarized with existing work in this domain and will have to prepare presentations based on peer-reviewed publications in some of the highest ranked journals in the field.

Important information for students planning on completing the entire specialization Strategic Management, i.e. those who want to enroll for the Major as well:
This course is NOT compatible with “Experimental Methods – Laboratory Experiments”. That means that if you complete this course (“Experimental Methods I: Agent Based Modelling in Organisations”), you are expected to continue with “Experimental Methods II: Agent Based Modelling in Organisations”, which is the corresponding follow-up class in the Major. You should NOT switch between those two streams, as the topics discussed are entirely different and you will not be able to participate meaningfully in any follow-up course if you haven’t completed the corresponding Minor-class.

This course is meant to be interactive and is built around the idea of a laboratory setup as is typical for social sciences. The setup necessitates certain software and IT equipment and in order to provide every student with the same opportunity to successfully participate in the course, it is typically held in one of the PC-labs at OMP 1.
Due to the current situation related to Covid-19, however, it may be necessary that some (or all) sessions are held in an online format. The decision to do so will depend on university guidelines and ongoing developments. If sessions will be conducted remotely, the same timeslots will be used as planned for on-site meetings. Given capacity restrictions of the PC-labs and also in order to maintain a high level of quality and fairness, the number of participants admitted to register for the class will be limited, regardless of the sessions being online or in presence.

Art der Leistungskontrolle und erlaubte Hilfsmittel

10% - In-class Participation
25% - Homework Assignments
25% - Paper Presentation
40% - Final Exam

Note that for the Paper Presentations, students will work together in groups and submit a video recording of their presentation.
The Final Exam will be a 2-hour open-book exam.
More detailed information will be provided during the course.

Mindestanforderungen und Beurteilungsmaßstab

Please note that attendance during the first session is absolutely mandatory.
Missing the first session without prior written notice to the lecturer (at least 24 hours before the start of the session) providing a relevant reason/proof (e.g. doctor’s notice in case of illness) will result in deregistration from the course. In such cases the missing student’s place will be given to the person next in line on the waiting list (if this person is present in the first session).

In general, students are allowed to miss up to 10% (2.5 hours) of scheduled classes without any consequences. Exceeding this limit, however, will result in failing the class.

The grading scheme will look as follows:
5 – [0%;50%)
4 – [50%;62.5%)
3 – [62.5%;75%)
2 – [75%;87.5%)
1 – [87.5%;100%]

Prüfungsstoff

Students are expected to have understood all topics discussed and presented in class.

Literatur

Relevant literature will be discussed in class.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Di 14.03.2023 11:28