Course Schedule

Start > Promotionsstudium Fakultät Management und Technologie / doctoral courses Faculty of Management and Technology (Promotion / doctorate) -> Promotionskolleg Wirtschaftsinformatik -> Forschungsmethoden Wirtschaftsinformatik

Lehrveranstaltungen

Introduction to statistics (Seminar)

Dozent/in: Henrik Wehrden

Termin:
 Einzeltermin | Mo, 11.09.2023, 08:30 - Mo, 11.09.2023, 17:30 | C 40.606 Seminarraum
Einzeltermin | Di, 12.09.2023, 08:30 - Di, 12.09.2023, 17:30 | C 40.606 Seminarraum
Einzeltermin | Mi, 13.09.2023, 08:30 - Mi, 13.09.2023, 17:30 | C 40.606 Seminarraum

Inhalt: Introduction to statistics

Qualitative Research Methods (Seminar)

Dozent/in: Markus Reihlen

Termin:
 Einzeltermin | Di, 05.09.2023, 09:00 - Di, 12.09.2023, 17:00 | C 6.026 Seminarraum
Einzeltermin | Mi, 06.09.2023, 09:00 - Mi, 13.09.2023, 17:00 | C 6.026 Seminarraum
Einzeltermin | Do, 07.09.2023, 09:00 - Do, 14.09.2023, 17:00 | C 6.026 Seminarraum

Inhalt: Qualitative research is a research strategy that emphasizes large bodies of unstructured data (textual, graphical, audio, and video data) that cannot be meaningfully analyzed by formal, statistical approaches. Despite differences, qualitative research approaches share at least the following two assumptions: (1) by systematically generating and analyzing data new theory can be discovered (inductive view), and (2) this theory stresses the understanding of the socio-economic world through an examination of interpretation of that world by its participants. Since each particular research method is informed by different philosophical traditions, this course will first introduce different perspectives on the socio-economic research process like positivism, interpretativism, realism, and postmodernism. Students will then learn how to set up a qualitative research project with particular emphasis on the case study approach. Case studies offer rich, empirical descriptions of particular examples of a phenomenon that are typically based on a variety of data sources. The case-study method involves using one or more cases to create case-based, empirical evidence used for a subsequent theory building. In order to build theory from case study data, students will be made familiar with the grounded theory, which is a general method of comparative analysis for qualitative data. The idea of the grounded theory is to develop theoretical categories, propositions, and mid-range theories based on a particular inductive method for qualitative data analysis. This data analysis is greatly supported by different software packages. While the course will provide an overview of existing software programs, students will be introduced in particular to the Atlas.ti platform. The course is designed as a doctorate workshop. Throughout the course, initiative, creativity, and critical thinking on part of the students will be appreciated and encouraged.

Think Mathematically, Act Algorithmically: Optimization Techniques (Seminar)

Dozent/in: Paolo Mercorelli

Termin:
 wöchentlich | Freitag | 16:00 - 18:00 | 07.04.2023 - 07.07.2023 | C 40.106 Konrad-Zuse-Raum | Info! Diese Veranstaltung ist eine gemeinsame Veranstaltung von Master Komplementär- und Promotionsstudium

Inhalt: MATLAB is a platform for scientific calculation and high-level programming which uses an interactive environment that allows to conduct complex calculation tasks more efficiently than with traditional languages, such as C, C++ and FORTRAN. It is the one of the most popular platforms currently used in the sciences and engineering. Optimization techniques can be applied in a wide interdisciplinary range of applications in control, estimation and identification problems. Using Matlab, the course embraces the most important optimization techniques and methods which can be used in control systems. The proposed techniques, e.g. Model Predictive Control, Two Point Boundary Optimization Problem, etc. are implemented using Matlab/Simulink. Through discussions on the mathematical origin of the proposed techniques and methods and their inspiring ideas the students should reach, not only a good command on the software, but also a critical spirit to interpret the nature of the algorithms and to reflect on their foundations and structures.