Stand: WiSe 2023
| 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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| Lehrende |
Weiden, Henrike (Prof. Dr., LL.M.)
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| Prüfung(en) |
Prüfungsform: ModA
Detailangaben: Term paper at the end of the semester, see syllabus for details.
Hildsmittel:
Prüfende:
Weiden, Henrike (Prof. Dr., LL.M.)
, Anderl, Eva (Prof. Dr.)
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| Lehr- und Lernform(en) |
| 4 SWS | S - 1 Angebot(e)
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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 · Identification and analysis of selected legal obstacles · Application of the given framework to a business model · Potentially presentation in public
Applied methods in Economics and Business administration ❒ Analysis models and methods (research and analysis models): · Legal analysis · Business model 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 · Potentially Lego Workshop and/or Learning Lab Workshop · Case studies · Literature reviews · Potentially field trip · Presentation (potentially in public)
Literature: · Introduction to and identification of currently relevant literature will be part of the class. |
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