Educational Journey
Educational Journey
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
The Educational Journey covers lectures at a foreign university, company visits, and leisure activities. Course topics change from semester to semester.
- Planning security: Even if the study trip cannot take place, there is the possibility that you can acquire the 3 ECTS through an alternative examination performance
Assessment Methods
Written exam (60min)
Grade
The trip typically lasts from Monday to Friday/Saturday (including travel). A detailed schedule will be announced during a kick-off session at the University of Liechtenstein in May. Attendance at all days and events is mandatory.
Digital Innovation
Digital Innovation
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
Digital Innovation covers the fundamentals of digital innovation and the development and implementation of novel and original solutions in which the innovation process, its outcomes, or the ensuing organisational and social transformation is embodied in or enabled by digital technologies. Digital Innovation is one of the core topics of the degree programme, so the course also provides a basis on which students can choose their electives. The course covers six primary topics:
• Fundamental properties of digital technologies and digital innovation
• Organising for digital innovation
• Digital platforms and ecosystems
• Digital innovation and capital creation
• Digital business models
• Digital entrepreneurship
• Fundamental properties of digital technologies and digital innovation
• Organising for digital innovation
• Digital platforms and ecosystems
• Digital innovation and capital creation
• Digital business models
• Digital entrepreneurship
Teaching Method
• The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
• Case studies are used to discuss the course contents. Contemporary scientific publications from Information Systems and Management are discussed in class.
• Case studies are used to discuss the course contents. Contemporary scientific publications from Information Systems and Management are discussed in class.
Learning Results
After successful completion of the course, students will
Professional competence
• understand the basics of the fundamentals of digital innovation and the development and implementation
of novel and original solutions that are relevant to the field of information systems
• understand the main concepts, theories, and methods related to digital innovation
Methodological competence
• be able to apply the understanding and the methods into their projects or illustrative cases
• be able to analyse the role of digital technologies in existing business models
• be able to develop business models that consider options created through digital technologies
Social competence
• be able to collaborate and work in teams
• support each other during the learning process
Personal competence
• critically reflect on technological outcomes
Professional competence
• understand the basics of the fundamentals of digital innovation and the development and implementation
of novel and original solutions that are relevant to the field of information systems
• understand the main concepts, theories, and methods related to digital innovation
Methodological competence
• be able to apply the understanding and the methods into their projects or illustrative cases
• be able to analyse the role of digital technologies in existing business models
• be able to develop business models that consider options created through digital technologies
Social competence
• be able to collaborate and work in teams
• support each other during the learning process
Personal competence
• critically reflect on technological outcomes
Assessment Methods
Written exam (90min)
Digital Humanities
Digital Humanities
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
Digital Humanities stands at the intersection between digital technology and social action – between computing and humanities. Besides enabling digital innovation, digital technology has fundamentally changed the way we see the world, work, and socialise. We are increasingly challenged to make sense of data and information, and turn them into things we can use for different goals. On the other hand, we also need to adjust ourselves in order to collaborate with each other through digital technology – and sometimes even with digital technology itself. How far should we go? How do we find a balance? This course is primarily concerned with understanding different and sometimes contradicting views on the relationship between digital technology and social action. The course covers five primary topics:
• Introduction to digital humanities
• The computational turn
• Favourable views on digitisation and digitalisation
• Critical views on digitisation and digitalisation
• Examples of digital humanities projects
• Introduction to digital humanities
• The computational turn
• Favourable views on digitisation and digitalisation
• Critical views on digitisation and digitalisation
• Examples of digital humanities projects
Teaching Method
• The module involves interactive lectures with exercises to integrate theoretical knowledge with critical analysis skills.
• Case studies are used to discuss the course contents.
• Recent scientific publications from Information Systems and Digital Humanities are discussed in class.
• Case studies are used to discuss the course contents.
• Recent scientific publications from Information Systems and Digital Humanities are discussed in class.
Learning Results
After successful completion of the course, students will
Professional competence
• understand the basic concepts and underlying theories related to digital humanities
• understand different and sometimes contradicting views on the relationship between digital technology
and social actions
Methodological competence
• be able to analyse everyday examples based on these initial understandings
Social competence
• be able to collaborate in teams and support each other during the learning process
Personal competence
• be able to reflect on their own relationship with digital technology
Professional competence
• understand the basic concepts and underlying theories related to digital humanities
• understand different and sometimes contradicting views on the relationship between digital technology
and social actions
Methodological competence
• be able to analyse everyday examples based on these initial understandings
Social competence
• be able to collaborate in teams and support each other during the learning process
Personal competence
• be able to reflect on their own relationship with digital technology
Assessment Methods
Written exam (60min)
Digital Business
Digital Business
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
In Digital Business, students collaborate with small and medium-sized companies to develop new business models, open new markets, and innovate with existing products and services, so students learn to recognise, understand, develop, and exploit digital innovations. The course topics change from semester to semester, but the course usually addresses seven grand themes:
• Designing digital business strategy
• Digital entrepreneurship and intrapreneurship
• Opportunity recognition
• Business model innovation
• Value creation and cocreation
• Digital transformation
• Project management
• Designing digital business strategy
• Digital entrepreneurship and intrapreneurship
• Opportunity recognition
• Business model innovation
• Value creation and cocreation
• Digital transformation
• Project management
Teaching Method
• The course involves interactive seminars with workshops and regular presentations.
• The faculty and a jury of representatives from regional companies evaluate the students’ solutions in terms of innovativeness and usefulness and provide them with feedback and advice.
• The faculty and a jury of representatives from regional companies evaluate the students’ solutions in terms of innovativeness and usefulness and provide them with feedback and advice.
Learning Results
After successful completion of the course, students will
Professional competence
• understand the complex nature of digitalisation in small and medium-sized enterprises as well as start-up
ventures
• understand the entrepreneurial aspects in digital business: from opportunity recognition to designing digital strategy and business model and convincing potential stakeholders
Methodological competence
• be able to develop feasible solutions to their identified issues and evaluate them using appropriate methods
Social competence
• be able to collaborate in teams and with external partners
• be able to outline a project plan to implement their ideas and complete the project under time pressure
Personal competence
• demonstrate readiness to innovate and to view an idea, a problem, or a solution from several different
angles
• be able to articulate their ideas clearly in an elevator pitch, in order to persuade potential collaborators
and sponsors of the values of their ideas
Technological competence
• be able to identify the appropriate technologies to support digital business solutions
Professional competence
• understand the complex nature of digitalisation in small and medium-sized enterprises as well as start-up
ventures
• understand the entrepreneurial aspects in digital business: from opportunity recognition to designing digital strategy and business model and convincing potential stakeholders
Methodological competence
• be able to develop feasible solutions to their identified issues and evaluate them using appropriate methods
Social competence
• be able to collaborate in teams and with external partners
• be able to outline a project plan to implement their ideas and complete the project under time pressure
Personal competence
• demonstrate readiness to innovate and to view an idea, a problem, or a solution from several different
angles
• be able to articulate their ideas clearly in an elevator pitch, in order to persuade potential collaborators
and sponsors of the values of their ideas
Technological competence
• be able to identify the appropriate technologies to support digital business solutions
Assessment Methods
Seminar paper, presentations, project results; attendance is mandatory (80%)
C15 Educational Journey 2022 - War between Russia and Ukraine - Implications on the Financial Industry
C15 Educational Journey 2022 - War between Russia and Ukraine - Implications on the Financial Industry
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Finance
Master's degree programme in Finance
Project Description
Master students have the opportunity to take part in educational journeys to the world’s most important financial centres. Taking place
Teaching Method
Excursion
Learning Objectives
After successfull completion of this module, students
- know the role of international enterprises and organizations including banks, asset or hedge fund management services, portfolio managers, insurance companies, chambers of foreign trade, chambers of commerce, supranational organisations, ambassadors, politicians or universities in structuring the competitiveness of a financial market;
- know the specifities of the visited financial market;
- established an international and intercultural network.
Assessment Methods
See lecture within the module.
Module 5 - Advanced Digital Innovation
Module 5 - Advanced Digital Innovation
Module Coordinator/Lecturers
Study Programmes
Certificate programme Digital Legal Officer
Project Description
Ob Crowdfunding und Crowdlending, Online-Zahlungsdienste, Robo Advice, der Einsatz künstlicher Intelligenz, RegTech oder auch Outsourcing in die Cloud – all diese Themen bringen eine Vielzahl regulatorischer und aufsichtsrechtlicher Fragestellungen mit sich. Anhand der aktuellen Rechtsentwicklung mit besonderem Fokus auf das EWR-Recht, werden die damit verbundenen An- und Herausforderungen analysiert und darauf aufbauend mittels praxisbezogener Fallbeispiele Best Practices und Methoden zur Bewältigung dieser vielfältigen Aufgaben vermittelt.
Learning Results
-Wissen und Verstehen:
Die Teilnehmende verfugen uber vertieftes Wissen im Bereich der digitalen Innovationen. Sie kennen die Unterschiede, Vorteile und Herausforderungen der jeweiligen technologischen Modelle, wie diese einzusetzen sind, welche Schnittstellen es gibt, und verstehen komplexe Aufgabenstellungen.
-Anwendung von Wissen und Verstehen:
Die Teilnehmende sind in der Lage, regulatorische und aufsichtsrechtliche Fragen auf hohem Komplexitatsniveau zu verstehen und Losungen zu erarbeiten. Sie erkennen Herausforderungen, verstehen die sich daraus ergebenden Rechtsfolgen und konnen selbstandig Losungsstrategien entwickeln.
-Urteilen:
Nach Abschluss dieses Moduls sind die Teilnehmenden fahig, relevante Sachverhalten zu analysieren und zu beurteilen. Sie erkennen neue Moglichkeiten und damit verbundene Herausforderungen und konnen diese nach regulatorischen und aufsichtsrechtlichen Aspekten beurteilen.
-Kommunikative Fertigkeiten:
Die Teilnehmenden sind fahig, unterschiedliche Ansatze zielgruppengerecht zu kommunizieren, auf andere Argumente einzugehen und diese zu begrunden und zu verhandeln. Sie identifizieren die mit digitalen Innovationen verbundenen An- und Herausforderungen und konnen notwendige Massnahmen klar und eindeutig kommunizieren.
-Selbstlernfahigkeit:
Die Teilnehmenden finden sich in der Welt der digitalen Innovationen zurecht und konnen sich selbstandig mit der damit verbundenen rechtlichen und aufsichtsrechtlichen Aufgabenstellung in der Praxis auseinandersetzen. Sie erkennen Losungsmoglichkeiten und wissen diese in Unternehmen umzusetzen.
Die Teilnehmende verfugen uber vertieftes Wissen im Bereich der digitalen Innovationen. Sie kennen die Unterschiede, Vorteile und Herausforderungen der jeweiligen technologischen Modelle, wie diese einzusetzen sind, welche Schnittstellen es gibt, und verstehen komplexe Aufgabenstellungen.
-Anwendung von Wissen und Verstehen:
Die Teilnehmende sind in der Lage, regulatorische und aufsichtsrechtliche Fragen auf hohem Komplexitatsniveau zu verstehen und Losungen zu erarbeiten. Sie erkennen Herausforderungen, verstehen die sich daraus ergebenden Rechtsfolgen und konnen selbstandig Losungsstrategien entwickeln.
-Urteilen:
Nach Abschluss dieses Moduls sind die Teilnehmenden fahig, relevante Sachverhalten zu analysieren und zu beurteilen. Sie erkennen neue Moglichkeiten und damit verbundene Herausforderungen und konnen diese nach regulatorischen und aufsichtsrechtlichen Aspekten beurteilen.
-Kommunikative Fertigkeiten:
Die Teilnehmenden sind fahig, unterschiedliche Ansatze zielgruppengerecht zu kommunizieren, auf andere Argumente einzugehen und diese zu begrunden und zu verhandeln. Sie identifizieren die mit digitalen Innovationen verbundenen An- und Herausforderungen und konnen notwendige Massnahmen klar und eindeutig kommunizieren.
-Selbstlernfahigkeit:
Die Teilnehmenden finden sich in der Welt der digitalen Innovationen zurecht und konnen sich selbstandig mit der damit verbundenen rechtlichen und aufsichtsrechtlichen Aufgabenstellung in der Praxis auseinandersetzen. Sie erkennen Losungsmoglichkeiten und wissen diese in Unternehmen umzusetzen.
Assessment Methods
Gruppenarbeit: Fallstudie inkl. Präsentation
Data Science
Data Science
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
Data Science covers statistical and exploratory techniques that are used to make sense of the vast and complex data sets that have emerged in business. Data Science is one of the core topics of the degree programme, so the course also provides a basis on which students can choose their electives. Students learn to detect patterns in large data sets in quantitative and qualitative formats to translate them into actionable insights. The course covers seven primary topics:
• Data visualisation and exploration
• Supervised learning techniques for regression (e.g. logistic regression)
• Supervised learning techniques for classification (e.g. classification trees)
• Unsupervised learning techniques (e.g. clustering, dimensionality reduction)
• Fundamentals of deep learning
• Text mining (e.g. topic modelling)
• Hands-on labs with Python
• Data visualisation and exploration
• Supervised learning techniques for regression (e.g. logistic regression)
• Supervised learning techniques for classification (e.g. classification trees)
• Unsupervised learning techniques (e.g. clustering, dimensionality reduction)
• Fundamentals of deep learning
• Text mining (e.g. topic modelling)
• Hands-on labs with Python
Teaching Method
• The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
Learning Results
After successful completion of the course, students will
Professional competence
• understand the basic concepts and methods of data mining and predictive analytics
• be able to assess the assumptions and quality of statistical models
Methodological competence
• know and be able to select and apply the right statistical models for a given task or data set
• be able to derive actionable insights from statistical results
• know basic visualisation and storytelling techniques
Social competence
• communicate effectively using visualisations
• understand different stakeholder perspectives in a data mining project
Personal competence
• critically reflect on analytical outcomes
• improve and mitigate self-inflicted errors
Technological competence
• be able to use Python including their libraries such as scikit-learn and matplotlib to apply machine learning
and to create visualisations
Professional competence
• understand the basic concepts and methods of data mining and predictive analytics
• be able to assess the assumptions and quality of statistical models
Methodological competence
• know and be able to select and apply the right statistical models for a given task or data set
• be able to derive actionable insights from statistical results
• know basic visualisation and storytelling techniques
Social competence
• communicate effectively using visualisations
• understand different stakeholder perspectives in a data mining project
Personal competence
• critically reflect on analytical outcomes
• improve and mitigate self-inflicted errors
Technological competence
• be able to use Python including their libraries such as scikit-learn and matplotlib to apply machine learning
and to create visualisations
Assessment Methods
Written exam (90min)
BPM and Organizational Practice
BPM and Organizational Practice
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Information Systems
Project Description
BPM and Organisational Practice explores Business Process Management (BPM) through an organisational-studies lens, so it is a BPM elective. Emphasizing the duality of stability and change in organisational work, the course covers the factors, mechanisms, and interventions that affect how processes behave over time. The course covers six primary topics:
• Organisation theory
• Process- and practice-based research
• Organisational routines
• Intra-organisational dynamics and endogenous change
• Organisational learning, unlearning, and forgetting
• The role of agency and intention in the execution of organisational work
• Organisation theory
• Process- and practice-based research
• Organisational routines
• Intra-organisational dynamics and endogenous change
• Organisational learning, unlearning, and forgetting
• The role of agency and intention in the execution of organisational work
Teaching Method
The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
Learning Results
After successful completion of the course, students will
Professional competence
• understand the key assumptions and management implications of BPM
• understand key assumptions about process work from organisation theory
• understand the main concepts of (strong) process theory
• understand the main competence of routine dynamics theory
Methodological competence
• be able to synthesize the main tenets of two different scientific fields (BPM and routine dynamics)
• be able to analyse organisational phenomena through the lens of (strong) process theory
• be able to attend to (subtle) social dynamics evolving throughout organising processes
Social competence
• Be able to change roles when addressing managerial questions (role as BPM expert versus role as organisation theorist)
• Be able to work together with colleagues on case assignments
Personal competence
• Be able to find unconventional approaches to BPM-related question
• Be able to reflect on strengths and weaknesses from specific scientific fields
Technological competence
• Know about ways to observe and measure process dynamics
Professional competence
• understand the key assumptions and management implications of BPM
• understand key assumptions about process work from organisation theory
• understand the main concepts of (strong) process theory
• understand the main competence of routine dynamics theory
Methodological competence
• be able to synthesize the main tenets of two different scientific fields (BPM and routine dynamics)
• be able to analyse organisational phenomena through the lens of (strong) process theory
• be able to attend to (subtle) social dynamics evolving throughout organising processes
Social competence
• Be able to change roles when addressing managerial questions (role as BPM expert versus role as organisation theorist)
• Be able to work together with colleagues on case assignments
Personal competence
• Be able to find unconventional approaches to BPM-related question
• Be able to reflect on strengths and weaknesses from specific scientific fields
Technological competence
• Know about ways to observe and measure process dynamics
Assessment Methods
Written exam (60min)
Sustainable Finance I
Sustainable Finance I
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Finance
Project Description
- Current and past developments in sustainable finance
- ESG data, data providers and materiality
- Environmental and social impact
- Channels of action: primary and secondary market, direct investments, real estate, politics
- Tools of action: positive and negative screening, ESG integration, proxy voting and engagement, green bonds and loans, political influence
- Regulatory frameworks and initiatives
Teaching Method
Lecture
Learning Results
- Student will describe, understand and discuss past and current developments in sustainable finance
- Students acquire a basic understanding of Sustainable EU-Regulation
- Students understand the structure, challenges and alternative providers of ESG data
- Students can distinguish between different types of sustainable finance products and investment strategies
- Students understand and can apply the concept of materiality
Seminar In Finance
Seminar In Finance
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Finance
Project Description
- Risk modelling
- Strategical and tactical asset allocation
- International diversification
- Forecasting moments of asset returns
- Foreign exchange rate risks and management
- Portfolio management
- Performance analysis
- Behavioural finance
- Dividend policy
- Company valuation
- Legal and tax issues in financial decisions
Teaching Method
Seminar
Learning Results
- Students have at their command detailed knowledge of finance and have a critical understanding of the procedures and methods in the subject area
- Compiling and utilising available sources in order to acquire an overview of previously unfamiliar sub-areas
- Preparing research papers on assigned topics or shorter empirical or analytical research projects by applying exacting technical procedures and methods
Course Materials
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