Teaching

We conduct research on the intersection between digital entrepeneurship, digital ecosystems, and organizing data and knowldedge. We will provide multiple courses that help to explain changes on firm- and ecosystem levels using multiple theories and methodologies. Our teaching is usually highly interactive and builds upon concepts of blended learning, oftentimes 'flipping the classroom'. It is important to us to not only reflect latest findings of information systems research with our students but also to work together on applying that knowledge. 

Our teaching extends to Bachelor, Master, PhD and Postdocs. Offers for PhD and PostDocs will be more clearly defined in the following months.

Winter 25/26

Digital Ideation and Entrepreneurial Design

Lecture & Exercise

Digital Ideation and Entrepreneurial Design

Lecturer:
  • Prof. Dr. Hannes Rothe
  • Daniel Courtney, M.Sc.
Contact:
Term:
Winter Semester 2025/2026
Cycle:
WiSe
Time:
Mondays, from 9:00 – 13:00 (planned to start end of November)
Room:
R12 R04 B21
Language:
English

Description:

Are you eager to apply your knowledge in a hands-on setting that mirrors the fast-paced startup world? Do you want to explore how digital ideas evolve into real ventures? If so, Digital Ideation and Entrepreneurial Design is the course for you!

The course Digital Ideation and Entrepreneurial Design introduces students to the basics of digital entrepreneurship and sustainable innovation with a focus on digital ideation and entrepreneurial design. Conducted in a practice-oriented approach, students work in teams to tackle real-world challenges provided by an external collaborator in order to develop solutions themselves. 

In the course, you develop adequate strategies to find and assess problems of individual and societal significance. Building on methods of design thinking, you are introduced to design-oriented research methodology, where you learn to systematically define relevant solution spaces to solve these problems. Through this approach, you learn to analyze complex requirements under time pressure, systematically develop alternative decisions and reflect on possible options in different contexts. You systematically analyze possible causes of deviations from plans and develop suitable response measures.

Individually or in teams, you prepare written analyses and illustrate their decision-making processes to later on present them appropriately to various target groups. To mirror this methodological approach, you engage in the scenario of an entrepreneurial context that requires you to search (or design) an opportunity through means of effectuation. 

The course consists of an individual assignment (40% of the grade) and group case study project that involves methods of design-oriented research (60% of the total grade).

Learning Targets:

After the successful completion of the module, students will be able to After the successful completion of the module, students will be able to 

  • Employ methods of design thinking for innovation search (fit of problem and solution space)
  • apply a design-oriented research methodology from information systems and entrepreneurship research
  • explain opportunity design and opportunity search
  • apply an effectuation approach
  • differentiate principles of effectuation from the principles of causal logic
  • decide in which situations it makes sense to act according to effectuation logic
  • select and apply effectuation tools in a targeted manner

Outline:

  • Sustainability
  • Startups
  • Team work
  • Design Thinking
  • Digital Entrepreneurship
  • Innovative Entrepreneurship
  • Business research

Literature:

  • Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of management information systems, 24(3), 45-77.
  • Peffers, K., Tuunanen, T., & Niehaves, B. (2018). Design science research genres: introduction to the special issue on exemplars and criteria for applicable design science research. European Journal of Information Systems, 27(2), 129-139.
  • Sarasvathy, S. D. (2009). Effectuation: Elements of entrepreneurial expertise. Edward Elgar Publishing.
  • Seckler, C., Mauer, R., & vom Brocke, J. (2021). Design science in entrepreneurship: conceptual foundations and guiding principles. Journal of Business Venturing Design, 1(1-2).
  • Sein, M. K., Henfridsson, O., Purao, S., Rossi, M., & Lindgren, R. (2011). Action design research. MIS quarterly, 37-56.
  • Venable, J., Pries-Heje, J., & Baskerville, R. (2016). FEDS: a framework for evaluation in design science research. European journal of information systems, 25, 77-89.
  • Additional literature is provided in the first session of the class.

Methods of Assessment:

Portfolio

Formalities:

The course will be provided as a lecture and exercise; both must be taken for accreditation and successful completion.

Dates are currently being finalized:

  • November 24: 9:00-13:00
  • December 1: 9:00-13:00
  • December 15: 9:00-13:00
  • January 5: 9:00-13:00
  • January 12: 9:00-13:00
  • January 19: 9:00-13:00
  • January 26: 9:00-13:00

Make-a-thon planned for Dec 5-7th (single weekend occurrence) with course collaborators.

New Policy on LLMs and Transparency in Work Creation

We are implementing a new policy to ensure transparency and clarity in the creation of student works, especially those involving Large Language Models (LLMs) like GPT. This policy applies to all works, including seminar papers, thesis, and project reports, and is designed to foster academic integrity, rigor, and replicability in your research.

Key Changes:

  1. All works must present a clear and transparent account of the methods and tools used in their creation. This includes documenting any use of AI or LLMs in the process.
  2. When LLMs are used, students are required to submit the complete chat history. This includes both the prompts given to the LLM and its responses. Students should ensure that they use a single chat session, save it in its entirety, and send it separately along with their work. This will provide a comprehensive record of how the work was generated.
  3. In the methods chapter of your work, there must be a specific sub-chapter detailing the tools and methods used to support your writing and study. This is to ensure that all methods, including AI-based tools, are fully explained and their role in the creation process is clear.