Syllabus
Registration via LPIS
| Day | Date | Time | Room |
|---|---|---|---|
| Tuesday | 04/07/26 | 01:00 PM - 05:30 PM | D3.0.237 |
| Thursday | 04/09/26 | 09:00 AM - 01:30 PM | D4.0.250 |
| Thursday | 04/23/26 | 08:30 AM - 01:00 PM | D2.0.334 Teacher Training Lab |
| Tuesday | 04/28/26 | 01:00 PM - 05:30 PM | TC.4.28 |
| Thursday | 04/30/26 | 08:30 AM - 01:00 PM | TC.4.28 |
Business and economics researchers are often concerned with seeking an in-depth understanding of the decisions individuals and groups make, the goals they pursue, the practices they engage in, or the relationships they form with colleagues, brands, consumption communities, and etc. Quantitative researchers analyze psychological mechanisms, identify surprising effects, or highlight human biases through experiments, surveys, or analysis of large databases.
Qualitative researchers, in contrast, explore, analyze, and theorize in depth how and why consumers, managers, employees, and others participate in market exchanges in specific ways. Instead of looking for significance in quantitative data, they study human experiences, attitudes, or practices directly. They observe behaviors, ask deep questions, and interpret unstructured data from a wide range of on- and offline sources to understand (rather than measure) how and why social life unfolds in certain ways.
This seminar provides doctoral and PhD students with an opportunity to intellectually engage with the philosophy and key concepts of qualitative research but more importantly with the practical dimension of in conducting (and publishing) qualitative work. Participants will learn how to critically evaluate published qualitative work, develop their own research questions, design qualitative research projects, collect and analyze data, and communicate their findings in compelling ways to make impactful theoretical and practical contributions to their respective fields of knowledge.
After completing this course, students will be able to
- demonstrate a solid understanding of the philosophy and key concepts of qualitative research,
- understand and critically appraise published qualitative work,
- develop meaningful research questions,
- design qualitative research projects to address their research questions,
- collect and analyze non-numerical data of various kinds,
- discuss strategies of conveying their findings to journal reviewers and editors, and
- discuss the practical and ethical complexities of conducting qualitative research.
Participation in the first session is mandatory. Of the other sessions, one may be missed.
The course will involve a mixture of lecturer presentations, participant presentations, academic article discussions, and practical exercises.
Assessment Overview:
1) Topic Presentation & Essay: 60 points
2) Paper Discussion: 20 points
3) Class Participation: 20 points
Details Assessment 1: Topic Presentation & Essay (60 Points)
Each participant will contribute to the class with a focused introduction of one focal theme related to qualitative research. This input will have two parts: 1) a short essay (12 pages max., Arial, 12 pt., double-spaced, including references) and 2) a 30 mins presentation (incl. discussion) of the key insights gained about the topic. Both parts jointly account for 60 points. Please submit both essay and presentation deck (if slides will be used) before the assigned presentation day.
For the essay, participants will be asked to
- review the relevant literature on the assigned topic,
- identify a relevant angle, or key dimensions, to synthesise the literature (e.g., competing definitions of the phenomenon, diverging assumptions on the nature of the phenomenon, diverging approaches to practical application)
- share examples of excellent academic application (if possible),
- use empirical examples for illustration (from the own or others scholars’ research),
- and include a reference list that serves fellow students as a point of departure if they want to know more about the topic.
For the presentation, participants will be asked to
- develop an engaging, inspiring presentation format (with our without slides). Interaction with the audience is encouraged, but given the short 30 mins presentation time, prolonged in-class exercises are discouraged,
- and plan on leaving about 10 mins time for discussing the topic with their audience.
Details Assessment 2: Paper Discussion (20 Points)
The second key element of the course involves critically discussing academic top-journal publications that draw on qualitative research. To sharpen their skills in assessing published work (and learning from it for their own studies), participants will be asked to critically review one of the assigned articles and discuss their thoughts with the class. All participants are required to read all assigned articles to allow for lively discussions and critical debate.
Details Assessment 3: Class Participation (20 Points)
Finally, participants are encouraged to actively contribute to class discussions through sharing critical thoughts, challenging presenters in constructive ways, and engaging in practical exercises.
Grading Scheme:
100-90 - 1 (excellent)
89-80 - 2 (good)
79-70 - 3 (satisfactory)
69-60 - 4 (sufficient)
< 60 - 5 (fail)
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Prior experience with qualitative research is a plus but not a requirement.
PhD and doctoral students without prior experience but a keen interest in using qualitative methods are invited to participate.
The course will be taught by Univ.Prof. Dr. Marius Lüdicke, a qualitative consumer culture researcher.
Course Materials
The articles that will be discussed in-depth in class as well as all additional reading materials will be made available via Canvas.
Use of AI Tools
The use of Artificial Intelligence (AI) tools such as ChatGPT, Perplexity, or Gemini for various aspects of academic research is encouraged. Participants shall keep in mind that these tools are not fully reliable yet and often return false results presented with great “confidence”.
Participants in this course must declare if and how they have used AI for their assignments. Reflecting on the productive use of AI will be subject to class discussion and best practices will be shared.
Useful, state-of-the-art AI tools for different applications (including academic work) can be found here: https://theresanaiforthat.com/
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