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English I

English I

Module Coordinator/Lecturers
Study Programmes
Bachelorstudiengang Betriebswirtschaftslehre (BSc BWL 21) (01.09.2021)
Project Description
  • Communication skills
  • Writing skills
  • Business English
Teaching Method
  • Exercise with max. 30 participants
  • Group and individual work
  • Discussions and role plays
  • Presentations and mini-lectures
Module number:
5610779
Semester:
WS 23/24
ECTS Credits:
3
Courses:
28 L / 21 h
Self-study:
69 h
Sprache:
Englisch
Scheduled Semester:
2

Einführung in die Betriebswirtschaftslehre

Einführung in die Betriebswirtschaftslehre

Module Coordinator/Lecturers
Study Programmes
Bachelorstudiengang Betriebswirtschaftslehre (BSc BWL 21) (01.09.2021)
Project Description
Die Betriebswirtschaftslehre (BWL) ist eine Teildisziplin der Wirtschaftswissenschaften und beschreibt die Führung, Steuerung und Organisation eines wirtschaftlichen Betriebs oder Unternehmens und basiert grundsätzlich auf der Annahme, dass Güter knapp sind und somit ein ökonomischer Umgang mit eben diesen Gütern erforderlich ist. Ziel der "Einführung in die BWL" ist es, Entscheidungsprozesse in Unternehmen zu beschreiben, zu erklären und zu unterstützen. Dabei befasst sich die BWL mit der wirtschaftlichen Perspektive, fokussiert auf den Einzelbetrieb.
Das Modul umfasst die Vorlesung „Einführung in die Betriebswirtschaftslehre" sowie die dazugehörende Übung. Im Detail vermittelt das Modul ein Grundverständnis der wichtigsten Elemente von Unternehmen und deren Zusammenhänge. Zusätzlich werden Themen zum Unternehmertum (Entrepreneurship) aufgegriffen.
Module number:
5610769
Semester:
WS 23/24
ECTS Credits:
6
Courses:
56 L / 42 h
Self-study:
138 h
Sprache:
Deutsch
Scheduled Semester:
1

Beschaffung, Logistik & Produktion

Beschaffung, Logistik & Produktion

Module Coordinator/Lecturers
Study Programmes
Bachelorstudiengang Betriebswirtschaftslehre (BSc BWL 21) (01.09.2021)
Project Description
Im Modul "Beschaffung, Logistik & Produktion" werden grundlegende Konzepte, Modelle und Methoden der betrieblichen Leistungserstellung behandelt und in Übungen praktisch angewendet. Zu den wesentlichen Lerninhalten zählen: Grundlagen der betrieblichen Leistungserstellung (insb. wirtschaftliche Zielsetzungen, Transformationsebenen im Unternehmen, Faktor- und Prozessbetrachtung), Beschaffung (insb. Bedarfsermittlung, Make-or-Buy-Entscheidungen, Nachfrageprognose, Bestandsmanagement), Produktion (insb. Produktions- und Ablaufplanung, Prozessdesign, Produktionsmanagement, Qualitätsmanagement) und Logistik (insb. Standortplanung, Transport, Supply Chain Management)
Teaching Method
Vorlesung
Module number:
5610783
Semester:
WS 23/24
ECTS Credits:
3
Courses:
28 L / 21 h
Self-study:
69 h
Sprache:
Deutsch
Scheduled Semester:
3

Business Process Analysis

Business Process Analysis

Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Wirtschaftsinformatik (MSc WI 19) (01.09.2019)
Project Description
Business Process Analysis focuses on process analysis, covering approaches and methods for designing, analysing, and simulating processes in organisations. The course covers four primary topics:
  • Introduction to process analysis
  • Process modelling and design
  • Process flow analysis
  • Process simulation
Teaching Method
  • The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
  • The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.
Learning Results
After successful completion of the course, students will:
  • know how processes can be modelled, analysed, and simulated
  • know the basic methods of process modelling for analysing, designing, and implementing information systems in organisations
  • be able to use the methods of process flow analysis and simulation to analyse, design, and improve business processes in organisations
Literature
  • Compulsory reading:Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. (2018). Fundamentals of Business Process Management (2nd edition). Berlin, Germany: Springer. - Additional reading:vom Brocke, J., & Rosemann, M. (Eds.) (2014). Handbook of Business Process Management. New York, USA: Springer.
Assessment Methods
Written exam (60min)
Module number:
5409670
Semester:
WS 22/23
ECTS Credits:
3
Courses:
30 L / 23 h
Self-study:
68 h
Scheduled Semester:
3

Autonomous Tools, Design, and Innovation

Autonomous Tools, Design, and Innovation

Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Wirtschaftsinformatik (MSc WI 19) (01.09.2019)
Project Description
Autonomous design toolas are fundamentally changing how designers work across various industries. Autonomous design tools make independent design decisions and in, some cases, execute entire design processes. They employ technologies typically associated with artificial intelligence, including machine learning, pattern recognition, meta-heuristics, and evolutionary algorithms.

Autonomous design tools allow for the generation of a variety of diverse design artifacts, including next-generation computer chips, software for specific domains, three-dimensional virtual worlds, and large amounts of content for video games and feature films. The applications for such autonomous design tools are also expanding to other industries, such as mechanical engineering, aerospace, and architecture.

Instead of creating artifacts by directly manipulating their representations, designers select tools, decide on design parameters, set values for these parameters, and evaluate and learn from the analysis of the results the tools produce. Design work in such situations involves intense interaction with autonomous tools. Designers need to be mindful of the logic, capabilities, and limitations of the tools, and the algorithms these tools employ, and find ways to make sense of and deal with the often unanticipated outputs of such tools.

The course addresses this increasingly important role of autonomous design tools by

  • discussing the conceptual foundations of autonomous design tools;
  • discussing how autonomous design tools change the nature of work and the role of human designers;
  • analyzing examples of using autonomous tools in design practice;
  • providing hands-on experience in agent-based modelling for students to simulate the behavior of these tools; and
  • providing hands-on experience in using autonomous design tools for the design of virtual worlds.
Teaching Method
  • The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
  • The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.
  • Contemporary scientific publications from Information Systems, Management, and Computer Science are discussed in class.
  • The NetLogo software is used to model and simulate autonomous design agents.
  • Further software tools may be used throughout class.
Learning Results
After successful completion of the course, students will:

  • understand the main concepts, theories, and methods related to autonomous design tools
  • be able to analyze how autonomous design tools change work processes
  • be able to develop agent-based models for simulating autonomous design tools
Assessment Methods
Written exam (60min)
Module number:
5410600
Semester:
WS 22/23
ECTS Credits:
3
Courses:
30 L / 23 h
Self-study:
68 h
Scheduled Semester:
3

Advanced Machine Learning

Advanced Machine Learning

Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Wirtschaftsinformatik (MSc WI 19) (01.09.2019)
Project Description
Advanced Machine Learning covers several advanced topics in the field of machine learning and is concerned with requirements engineering in particular. Students learn to analyse certain types and large amounts of data. The course covers seven primary topics:

  • Requirements engineering for machine learning and business intelligence projects
  • Frequent patterns and association rules
  • Explaining decisions of machine learning models
  • Time series analysis
  • Anomaly detection
  • Fundamentals of computational efficiency and distributed and parallel computing
  • Hadoop ecosystems, with a focus on Spark and MLlib
Teaching Method
  • The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.
Learning Results
  • After successful completion of the course, students will:have deepened their understanding in the field of machine learning and acquired a larger set of machine-learning techniquesunderstand the challenges and solutions of processing large amounts of databe able to gather requirements for projects in the field of machine learning and business intelligence
Literature
  • Compulsory reading:Witten, H., Eibe, F., & Hall, M. (2016). Data Mining: Practical Machine Learning Tools and Techniques. Amsterdam, The Netherlands: Elsevier.Aggarwal, C.C. (2015). Data Mining: The Textbook. Heidelberg, Germany: Springer.
Assessment Methods
Written exam (60min)
Module number:
5409689
Semester:
WS 22/23
ECTS Credits:
3
Courses:
30 L / 23 h
Self-study:
68 h
Scheduled Semester:
3

MILSA for outgoing students (study abroad SS 2024)

MILSA for outgoing students (study abroad SS 2024)

Module Coordinator/Lecturers
Study Programmes
Bachelorstudiengang Betriebswirtschaftslehre (BSc BWL 12) (01.09.2012)
Masterstudiengang Finance (MSc FI 15) (01.09.2015)
Fakultätsübergreifende Wahlfächer (FAWA 14) (01.09.2014)
Masterstudiengang Wirtschaftsinformatik (MSc WI 19) (01.09.2019)
Bachelorstudiengang Architektur (BSc AR 19) (01.09.2019)
Master's degree programme in Architecture
Masterstudiengang Entrepreneurship und Management (MSc EM 20) (01.09.2020)
Masterstudiengang Finance (MSc FI 20) (01.09.2020)
Bachelorstudiengang Betriebswirtschaftslehre (BSc BWL 21) (01.09.2021)
Project Description
The MILSA mentoring program provides students with the opportunity to develop their intercultural awareness and intercultural learning as students and future professionals. The program is offered twice yearly with a duration of approx. twelve months. It starts in April respectively in October.
The mentoring program provides an immersive intercultural learning experience in an international location. Students' learning is supported by pre-departure and post-sojourn workshops, and by Skype interviews and guided blog writing during the study abroad. The mentor is lecturer of the University of Liechtenstein.
The pre-departure workshop introduces students to explore aspects of intercultural learning and helps them prepare for their experience in a different society and culture.
During the stay abroad, students will talk to the mentor via Skype and write guided blog contributions about their intercultural learning. They stay in contact and complete group task together. Upon their return, students meet with the mentor in a post-sojourn workshop to discuss and reflect upon their experiences and the importance of their intercultural learning for their future professional lives.
The subject includes content on notions of culture, interculturality, intercultural learning,
stereotypes, identities, cultural practices, and reflection and reflective writing.
The First Steps in Intercultural Learning Workshop is held before students depart. This workshop provides essential content, discussion and activities to prepare students for their intercultural learning, international experience and to guide their completion of assessment tasks.
The Coming Home Workshop takes place after students return from their stay abroad and allows them to reflect on their experience, particularly their intercultural learning and its
application to their future professional lives. Students also present their group assignment.
Teaching Method
Workshops, discussions, writing blog contributions, Skype interview, online survey
Learning Objectives
  • To acquire and improve intercultural learning skills
  • To reflect on expectations for study abroad
  • To reflect on and discuss experiences while studying abroad; to reflect on the
  • behaviours and values in the host and home cultures
  • To practice observation and reflection in writing and in conversation
  • To reflect on one's use of the language of the host country and other languages used during study abroad
  • To encourage students to think about the study abroad experience in terms of their professional life
Learning Results
  • To acquire and improve intercultural learning skills
  • To reflect on expectations for study abroad
  • To reflect on and discuss experiences while studying abroad; to reflect on the
  • behaviours and values in the host and home cultures
  • To practice observation and reflection in writing and in conversation
  • To reflect on one's use of the language of the host country and other languages used during study abroad
  • To encourage students to think about the study abroad experience in terms of their professional life
Literature
"Culture and the primary socialization process" by Janet Jackson"

Supplied during the course
Maximizing Study Abroad, A Students' Guide to Strategies for Language and Culture Learning and Use
By R. Michael Paige, Andrew D. Cohen, Barbara Kappler Mikk, Julie C. Chi, & James P. Lassegard, Minnesota University Press
Assessment Methods
Grading

Assessment tasks:
  • Attending the First Steps in Intercultural Learning and Coming Home workshops
  • Writing three blog contributions
  • Completing one peer group task
  • Filling in online survey

Compulsory attendance 100%
Examination
Grading

Assessment tasks:
  • Attending the First Steps in Intercultural Learning and Coming Home workshops
  • Writing three blog contributions
  • Completing one peer group task
  • Filling in online survey

Compulsory attendance 100%
Grade
Fakultätsübergreifendes Wahlfach:
Regeln für die Anmeldung: www.uni.li/cross-faculty
Module number:
5611308
Semester:
WS 23/24
ECTS Credits:
3
Courses:
30 L / 23 h
Self-study:
68 h
Sprache:
Englisch

Financial Statement Analysis

Financial Statement Analysis

Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Finance (MSc FI 20) (01.09.2020)
Project Description
The course aims to introduce students to the critical assessment of financial statements, such that they are able to understand managers’ motivation and capability to engage in earnings management. The assessment of firms’ accounting quality is essential for the reliability of cash-flow forecasts in the context of corporate finance and business valuation. Students will engage with current research in the area, and they will be able to understand the relevance of identifying managerial discretion in accounting choices for the analysis and valuation of companies. Students will work empirically with corporate finance data. This module prepares students for the modules «Alternative Investments» and «Corporate Finance».

Topics covered include (e.g.):

  • The analysis of financial statements
  • The decision-usefulness of accounting information
  • Determinants and managerial motivations for earnings management
  • Earnings smoothing
  • Audit quality and audit fees
  • Empirical research
Teaching Method
  • Seminar, consisting of a presentation and a term paper.
  • Moodle is used throughout the course to disseminate course material and for information and discussion
Learning Objectives
Students...

  • Know about the analysis of financial statements
  • Gather knowledge on the managerial leeway for the management of earnings
  • Understand the quality spectrum of financial reports
  • Learn about the role of the financial audit for accounting quality
  • Are able to apply empirical methods based on financial statement information
Literature
  • Robinson, Thomas R.; Henry, Elaine; Brouhaha, Michael A. (2020): International financial statement analysis. Fourth edition. Hoboken, New Jersey: Wiley
  • Palepu, Krishna G.; Healy, Paul M.; Peek, Erik (2019): Business analysis and valuation. Fifth edition, IFRS standards edition. Andover, Hampshire, UK: Cengage Learning EMEA.
Assessment Methods
See lecture within the module.
Module number:
5611464
Semester:
WS 23/24
ECTS Credits:
3
Courses:
28 L / 21 h
Self-study:
69 h
Sprache:
Englisch
Scheduled Semester:
1

Financial Markets

Financial Markets

Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Finance (MSc FI 20) (01.09.2020)
Project Description
  • Introduction to financial marketsInterest rates and bond pricesThe structure of interest ratesMarket efficiencyMonetary policyMoney marketsBond marketsMortgage marketsDerivative markets
Teaching Method
Interactive lecture
Learning Results
  • After completing this course, students...know how interest rates and bond prices are related and influence each otherknow different structures and theories of interest ratesare able to explain what market efficiency is and know evidence for different stagescan explain how monetary policy is used to influence financial marketsknow the dynamics of money, bond, derivatives and mortgage markets
Literature
Brealey, R., Myers, S., and Allen, F. (2017). Principles of corporate finance (12th ed.). New York, NY: McGraw Hill
Assessment Methods
see lecture(s) within the module
Module number:
5610579
Semester:
WS 23/24
ECTS Credits:
3
Courses:
28 L / 21 h
Self-study:
69 h
Sprache:
Englisch
Scheduled Semester:
1

Financial Economics

Financial Economics

Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Finance (MSc FI 20) (01.09.2020)
Teaching Method
Interactive lecture
Learning Results
  • After completing this course, students...understand basic principles in financial economics (e.g., absence of arbitrage) and can apply them in discrete-time markets,link absence of arbitrage, state prices, and risk-neutral probabilities in complete and in incomplete markets,understand the implications of portfolio restrictions in financial markets, understand the classical models of risk and risk aversion and apply them to financial decision-making,are familiar with consumption-portfolio models and their optimization in discrete time.
Literature
> LeRoy, S. F., & Werner, J. (2014). Principles of financial economics (2nd ed.). Cambridge: Cambridge University Press
Assessment Methods
See lecture(s) within the module
Module number:
5610595
Semester:
WS 23/24
ECTS Credits:
3
Courses:
24 L / 18 h
Self-study:
72 h
Sprache:
Englisch
Scheduled Semester:
1
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