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

• 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.

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

Written exam (60min)

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.

• 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.

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

Written exam (60min)

Network and System Security covers advanced security mechanisms in computer networks and systems and attacks against information systems. The course focuses on eight primary topics:

• Essential network-security protocols
• Attacks against common network protocols
• Security issues in web applications
• Security mechanisms in operating systems
• Advanced exploitation techniques

• 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.
• Lab exercises and programming assignments are used to support the acquisition of practical skills.

After successful completion of the course, students will:

• understand the typical attacks against various components of information systems
• understand the main network security protocols and their implementation
• understand the main preventive security mechanisms in operating systems

The following conditions need to be met prior to registering for the module:

• successful completion of the module "Data and Application Security"

Exercise: Lab assignments
Lecture: Written exam (60min??)

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

• 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.

• 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

Written exam (60min)

Just as the doctoral consortium, the summer school serves multiple purposes in the students' education: Whereas the doctoral consortium aims at presenting the own work to an international audience, the summer school is supposed to deepen the students' methodological skills. In addition, working together with professors and PhD students from abroad also contributes to developing the students' social and communicative skills in an international and intercultural environment.

In preparing their proposals and applications for a summer school, students will be assisted by lecturers of the Institute of Information Systems at the University of Liechtenstein. Accepted students will take part in the summer school. A reflection of the lessons learned at the summer school together with the lecturers is also part of the module.

The primary objective of the summer school is to get further insights into the research methods applied by the PhD students and to discuss evolving questions with other young scientists.

The students will be assessed in this module through:

• competitive selection process of the summer school
• specific mechanisms of the summer school

Module availability:
On application at an internationally renown summer school, such as organised e. g. by the European Research Center for Information Systems (ERCIS).

Just as the doctoral consortium, the summer school serves multiple purposes in the educational programme of the students: Whereas the doctoral consortium aims at presenting the own work in an international frame, the summer school intends to deepen methodological skills in a specific field of choice relevant to the PhD theses of the students. In addition, working together with professors and PhD-students from abroad also contributes to social and communicative skills of the students in an international and intercultural environment.

Doctorate entrepreneurship and management students participating in an international Ph.D. summer school study contemporary issues in research design and/or methodology.

The primary objective of the summer school is to get further insights into the research methods applied by the PhD students and to discuss evolving questions with other young scientists and leading experts in the field.

The students will be assessed in this module through:

• competitive selection process of the summer school
• specific mechanisms of the summer school

Module availability:
On application at an internationally renown summer school, such as organised e. g. by the Swiss National Science Foundation or Essex Summer School in Social Science Data Analysis and Collection.

Research Methods in International Financial Services can be very different, depending on the specific research area of Banking, Finance and Taxation. This module description is developed for a student with a need for advanced methods in econometrics. For students with different needs appropriate courses will be choosen and credited.

• Principles of Estimation and Testing
• Limited Dependent Variable Methods
• Longitudinal Data Models
• Stationary Time Series Models
• Stochastic Trends and Co-Integration

Lecture and self-study; presentation and paper by students is possible.

The module "Research Methods in International Financial Services " aims at deepening the students' competences regarding knowledge in their research design.

• This course should help - based on research methods offered on the master's level - to apply advanced econometric research methods, currently used by the research community.
• This course helps the student to independently develop a research concept for specific research questions.
• This course helps students to discuss methodological issues with colleagues working in the same area.

Students will be able to:

• Have an advanced overview of econometric principles for cross-sectional, panel, and time-series data sets.
• Apply econometric techniques in the area of microeconomics, macroeconomics and finance.

The students will be assessed in this module through:

• Written exam or presentation and paper (about 4000 - 5000 words)

In the Research Seminar course, students learn to apply in practice what they learned in the Research Methods course. The seminar covers issues related to identifying and formulating research questions, choosing a suitable research design to use in answering these questions, evaluating the feasibility of a planned research study, and writing research proposals. Together with faculty, students develop research proposals (so-called “exposés”) for their master’s theses

• The course involves interactive seminars with workshops and regular presentations.
• The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.

After successful completion of the course, students will:

• know what makes a good research topic and that the search for a research topic is a challenging endeavour
• know what methods can be applied to identify research ideas and refine them into research questions
• be able to develop research questions that are both practical and academically relevant
• be able to conduct systematic and effective literature reviews to demonstrate the novelty of their research ideas and provide background for their research
• develop qualitative, quantitative, mixed-method, and design-oriented research designs
• recognize and analyse the ethical problems in designing and conducting research in the field of Information Systems
• know how to consider issues of feasibility in planning their research studies
• be able to write effective research proposals

Seminar paper, presentation

In Research Methods, students learn to identify pertinent research questions, conduct systematic literature reviews, apply appropriate research methods, and report on their results. The course covers nine primary topics:

• Introduction to scientific research
• Scientific writing
• Ethical standards
• Literature reviews
• Qualitative research
• Quantitative research
• Mixed-methods research
• Design science research
• Theories used in Information Systems research

• The course involves interactive lectures with exercises to integrate theoretical knowledge, practical design, and analysis skills.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and for information and discussion.

After successful completion of the course, students will:

• understand the historical development and concept of scientific research.
• understand the fundamentals of scientific writing.
• be familiar with the most common issues related to research ethics, including plagiarism.
• will know the Association for Information Systems (AIS) Code of Research Conduct.
• be able to identify appropriate theories to explain empirical phenomena.
• be able to identify suitable research methods in order to seek answers to specific research questions.
• be able to use appropriate qualitative, quantitative, mixed-methods and design-oriented approaches to scientific research.

Written exam (60min)

The module "Research Methods in Information and Process Management Science" aims at deepening the students' skills in research design. It focuses on pivotal issues of conducting and structuring research activities as part of information and process management research.

Subjects dealt with in the module comprise (but are not limited to):

• Introduction into design science
• Design science vs. behavioural science
• Rigour vs. relevance
• Design science in information systems research
• The design science research process
• Reviewing the literature
• Design science examples
• Design science challenges
• Theorizing in design science
• Publishing design science

• Lecture
• Self-study
• Presentation by students

Students successfully participating in the module will

• know how to explain the design science approach as related to 'traditional' approaches in research,
• be able to differentiate between major constructs and issues in information systems research, such as relevance, rigour, truth, and utility,
• know about the major contributions on design science published in information systems research,
• be able to structure the design science research process,
• be capable of conducting rigorous literature reviews as part of design science research,
• know about major evaluation methods,
• be aware of the role of theories in design science research, and
• know the major information systems outlets for publishing design science research.

The students will be assessed in this module through:

• Presentations
• Discussions