Stand: SoSe 2025
| Name | Legal Issues for Data-driven Business | |
| Katalog-Nummer | FK 10#RE#M4.6 | |
| Zugehörigkeit zu Curriculum |
Master Betriebswirtschaft | M4.6 | 5 Leistungspunkte
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| Modulverantwortung |
Weiden, Henrike (Prof. Dr., LL.M.)
Anderl, Eva (Prof. Dr.)
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| Prüfung(en) |
Prüfungsform: ModA
Detailangaben: Term paper at the end of the semester, see syllabus for details. It is mandatory to take part in the lectures from the beginning of the semester to make sure all students are part of a team and all teams agree on the topic for the semester. No shows during the first month of the semester will not be entitled to submit a paper, thus will not be graded.
Hildsmittel:
Prüfende:
Weiden, Henrike (Prof. Dr., LL.M.)
, Wende, Susanne (Prof. Dr.)
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| Lehr- und Lernform(en) |
| 4 SWS | S - wird nicht angeboten
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| Arbeitsaufwand |
Präsenzzeit: 0 Stunden
Selbststudium, Vor- und Nachbereitung, Prüfungsvorbereitung: 0 Stunden
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Voraussetzungen
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none
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Verwendbarkeit
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| Inhalt / Lernziele |
Intended Learning Outcomes (Skills, Knowledge, Attitude) This class will enable students to identify legal issues related to digitized business models. Students will be acquainted with the selected topics within the legislative framework and apply basic strategies to avoid typical legal obstacles. Participants will learn to configure business models in a legally safe manner. The aim of the class is to provide the necessary insights and competences for legal compliance of digital business models. Moreover, students will work in small teams in an intercultural setting to develop solutions to assigned topics. This module helps students to understand the dependencies of digitization in a company with the corresponding legal requirements. Having completed this class, participants will be prepared to determine potential legal risks within the context scrutinized in class. They will be able to pinpoint typical questions and solve them accordingly.
Contents
· Selected legal regulations applicable to the digital economy with a strong focus on data privacy and the AI Act · Identification and analysis of selected legal issues · Application of the given framework to a business model
Applied methods in Economics and Business administration ❒ Analysis models and methods (research and analysis models): · Legal analysis ❒ Quantitative empirical methods (comparative – statistical, mathematical methods, data analysis): · Risk management process with respect to selected legal obstacles ❒ Qualitative and interpretative methods (expert interviews, polls, standardized surveys) · Qualitative analysis · Qualitative expert interviews
Teaching and Learning methods · Lectures/guest lectures · Literature reviews - Project-based work · Potentially field trip · Presentation - Potentially COIL project or collaboration with neighboring faculty
Literature: · Introduction to and identification of currently relevant literature will be part of the class. |
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