📌 Key facts
- What: This thesis investigates the psychological and behavioral factors influencing user acceptance of Generative AI systems focusing on the trade-off between personalization and privacy. It explores how users perceive the value of tailored AI-generated outputs versus the risks associated with data sharing and algorithmic transparency. The research aims to identify key drivers of trust, perceived usefulness, and comfort when interacting with GenAI tools in consumer contexts.
- When: Start anytime. Applications are open!
- How to apply: Send your CV, transcript of records, and a short statement of research interest (details below)
- 📌 Key facts
- 💡 Background
- 🦾Who We Are
- 🎯 Topics of Interest and Potential Outcomes
- 🎓 Profile
- 📝 How to Apply
💡 Background
Generative Artificial Intelligence (GenAI) is rapidly transforming how users interact with digital services, enabling personalized content creation, recommendations, and communication at scale. Organizations increasingly integrate GenAI tools into customer interfaces to enhance engagement and user experience.
However, this growing personalization raises concerns about privacy, data use, and transparency. Users often appreciate tailored interactions yet remain skeptical about how their data is collected and processed, creating a tension between personalization benefits and perceived privacy risks. Understanding this balance is essential for developing responsible AI applications that foster trust and long-term acceptance.
🦾Who We Are
The Chair for Strategy and Organization is focused on research with impact. This means we do not want to repeat old ideas and base our research solely on the research people did 10 years ago.
Instead, we currently research topics that will shape the future. Topics such as Quantum/Deep Tech, Agile Organisations and Digital Disruption, (Generative) Artifical Intelligence, Creativity and Innovation, Digital Transformation and Business Model Innovation, Diversity, Education Technology and Performance Management, HR-Tech, Leadership, and Teams. We are always early in noticing trends, technologies, strategies, and organisations that shape the future, which has its ups and downs.
🎯 Topics of Interest and Potential Outcomes
- Perceptions of AI upskilling effectiveness among employees and leaders
- Impact of AI upskilling on AI literacy, productivity, and employee empowerment
- Challenges and success factors in the implementation of AI upskilling programs
- Measurement approaches for outcomes beyond traditional KPIs (e.g., cultural change, innovation)
Potential outcomes:
- Systematic literature review
- Meta-analysis
- Conceptual model development
- Experimental design and field studies
🎓 Profile
- Strong interest in AI, digital transformation, and organizational development
- Reliable, structured, and self-driven working style
- Strong academic record and analytical mindset
📝 How to Apply
If you are interested, please contact Maximilian Rink by submitting your CV, grade report, preferred starting date & short motivation statement. Please also indicate which kind of thesis (= outcome) you are interested in.
