Simulation Methods: Computational Models in Management & Business Research
Seminar Empirics of Organizations
MBR Core Course
Computational modelling is an increasingly significant approach to theory development in management and economics. In general, simulations are commonly used for studying adaptive and evolutionary dynamics. However, they also have proven useful for the study of discrete dynamics as approximations to closed-form solutions. Simulations are also valuable for the numerical analysis of intractable analytical problems.
The Ph.D. course offers an introduction to computational methods and simulation models in management. It aims to introduce students to the basics of computational modelling, to give an overview of canonical simulation models and to discuss the potential and limitations of simulation models for management research. The main focus is on the discussion of original research. No prior programming experience is required for the course.
The course starts off with an introduction to formal models in the social sciences in general and computational modelling in particular (Day 1). Day 2 analyses and discusses learning and adaptation under uncertainty. Day 3 introduces social dynamics and agent-based modelling. Day 4 extends the analysis to adaptation in complex task environments. Day 5 discusses the modelling of evolutionary processes.
Note: A detailed syllabus will be distributed two weeks before the start of the course.
Your assignment for the course is to write a paper in your area that applies the concepts developed in the class. The paper should formulate a clear research question, provide a concise discussion of relevant prior models and outline a possible model structure and its intuition. The paper should be around ten pages and formatted according to Academy of Management guidelines. The deadline will be announced in class.
- The course is held in English
- Attendance to all lectures of the course is mandatory
- The number of participants is limited to 20
- In the mornings there will be lectures while during the afternoon's students will prepare for next days' sessions. On 29/01 students will, however, be able to attend the Quantitative Method's course.
|Dates||Mo. 26.01.- Fr. 30.01.2015; Room 307, Schackstr. 4/III|
|Credits||2 SWS in module A/I (Methods Course)|
|Examination||Class participation (30%)
Written assignment (70%)
A comprehensive list of reading material will be provided in the final course syllabus.