Supervision of a Bachelor thesis:
The research group Marketing & Sales (Prof. Dr. Martin Klarmann) offer supervision of Bachelor theses from various subject areas.
How can I apply?
There is no structured application process. You can approach the respective research group anytime using regular application documents (motivation, curriculum vitae, grades). Additionally, please state your preferred starting period.
Are there any requirements?
Completion of the module “Grundlagen des Marketing“ is required in order to be accepted for a Bachelor thesis at the institute. Additionally, it is recommended to have participated at the Bachelor seminar beforehand.
Which topics can be chosen?
Topics are in general very much tied to current research at the institute. As such, students have the opportunity to get an insight into the current research and are able to contribute. In general, all topics include an empirical part.
There are three options to get a topic:
Option 1: Offer
A list of currently offered topics can be found under this table. If you are interested in one of the topics listed, please contact the respective supervisor directly.
Option 2: Own topic/Open inquiry
We are open to own topic suggestions and open inquiries. Topic suggestions can be discussed with the potential supervisor.
Please contact Alessa Daumann (Research group Marketing & Sales) or the respective supervisor directly.
Required documents:
- Exposé of one page max (including the research question, theoretical anchor, and planned methodology)
- Curriculum Vitae
- Current grades
Option 3: Practical topic
Bachelor theses in cooperation with a company are possible.
Please contact Alessa Daumann (Research group Marketing & Sales) or the respective supervisor directly.
Required documents:
- Exposé of one page max (including the research question, theoretical anchor, and planned methodology)
Currently offered Bachelor thesis topics:
#1 How Consumers Use Voice Assistants in the Purchase Journey
Voice assistants such as Alexa, Siri, or Google Assistant are increasingly used in purchase-related situations (voice commerce), ranging from quick information searches to concrete product recommendations. This bachelor’s thesis examines the use of voice assistants along the customer journey through a qualitative interview study. The aim is to identify typical usage scenarios, motives, and perceived advantages and disadvantages, and to understand how these differ depending on product type and level of involvement (e.g., everyday purchases vs. expensive acquisitions). The thesis is expected to include a structured literature review (e.g., on voice commerce, information search, trust/privacy) as well as the conduct and analysis of interviews (including transcription and systematic analysis, e.g., thematic coding). Contact person: Alessa Daumann
#2 Do Explainable AI Recommendations Increase Decision Confidence?
AI-driven product recommendations are ubiquitous today, yet many users do not know why certain options are suggested to them. “Explainable AI” promises to close this gap. However, it remains unclear whether such explanations actually lead to better decisions (e.g., higher confidence, greater satisfaction, lower uncertainty) or whether they may also trigger skepticism (e.g., perceptions of manipulation or “too much influence”). This bachelor’s thesis experimentally investigates how explainable recommendations affect the decision process and decision outcomes. Optionally, the presentation of explanations can be varied (e.g., text vs. visualization vs. voice) and examined with regard to which formats are perceived as more helpful or credible. The thesis is expected to include a literature review (e.g., on trust in AI, explainability, recommender systems) as well as the design and implementation of an online experiment. Contact person: Alessa Daumann
#3 Consumer Reactions to AI Recommendation Errors
AI systems can provide helpful shortcuts in shopping contexts. At the same time, errors are inevitable (e.g., incorrect product features, wrong compatibility, or unsuitable recommendations). Such errors can trigger negative reactions and may damage long-term trust in AI assistance and in the providing brand. For both research and practice, it is therefore crucial to understand how consumers react to clear AI errors and which strategies are suitable for restoring trust. This bachelor’s thesis examines the effects of AI recommendation errors on consumer reactions such as anger, loss of trust, interaction abandonment, lower purchase intention, or choice deferral. Methodologically, an online experiment is well suited, complemented by a solid literature review on service failure, trust, and human-AI interaction. Contact person: Alessa Daumann
#4 Effects of Chatbot Communication Style on Purchase Decisions
Modern chatbots and AI assistants differ not only in their functions but also in their communication style: some communicate in a casual, humorous, and personal way (informal address), while others are deliberately factual, formal, and efficient. Such stylistic features may influence whether users perceive an assistant as likable, competent, or trustworthy. This bachelor’s thesis experimentally investigates how different communication styles of AI assistants affect perceptions of the assistant (e.g., warmth/likability, competence, trust) and purchase decisions. A scenario experiment can be implemented in which participants are randomly assigned to a style (humorous/informal vs. neutral/formal) and subsequently report evaluations and behavioral measures (e.g., purchase intention, choice confidence, choice deferral). For example, a focus on Gen Z (and Jugendsprache) could be incorporated. Contact person: Alessa Daumann
#5 Acceptance of Refurbished / Second-Hand Products in AI Recommendations
Refurbished and second-hand products are gaining importance, among other reasons due to price advantages and sustainability motives. At the same time, these products are often associated with uncertainties (e.g., quality risk, warranty issues, “used” stigma). When an AI actively recommends such products, this may foster acceptance by providing guidance and reducing perceived risk. This bachelor’s thesis investigates how consumers respond to AI recommendations of refurbished/second-hand products and which factors influence acceptance. Key constructs include perceived risk, trust in the recommendation, price attractiveness, and sustainability. The thesis is expected to include a literature review as well as the independent design and analysis of the study. Contact person: Alessa Daumann
