[HiWi] Supporting Employer Attractiveness Research for Blue-Collar Workers in German Manufacturing SMEs

Project Study or Master Thesis with <put the name of your company here>.

📌 Key facts

• What: We are looking for a student research assistant (HiWi) to support the funded research project DATA-KMU, a collaboration between the TUM Chair for Strategy and Organization and IPRI gGmbH (University of Ulm). Your main tasks will include coordinating and conducting qualitative interviews and focus groups with manufacturing SMEs and blue-collar workers, supporting web scraping and data analysis, and contributing to the development of a web-based employer attractiveness tool.
• Scope: Part-time, flexible hours
• When: Start asap. Applications are open!
• How to apply: Send your CV, transcript of records, and a short motivation statement (details below).

Please note: There is a German language requirement for this position, as you need to be able to conduct interviews and focus groups with SME representatives and blue-collar workers in German.

• 📌 Key facts
• 💡 Background
• 🦾Who We Are
• 🎯 Goals
• 🎓 Profile
• 📝 How to Apply

💡 Background

Germany's manufacturing sector faces a severe skilled-labor shortage — 600,000 positions in production remain unfilled, costing the economy an estimated EUR 50–65 billion annually in lost production capacity. Small and medium-sized enterprises (SMEs) are disproportionately affected: 93% of blue-collar positions are difficult or impossible to fill, and in micro-enterprises, 57% of vocational training slots go unfilled. Yet almost all existing research on employer attractiveness focuses on knowledge workers — whose needs, work environments, and motivations differ fundamentally from those of blue-collar workers on shop floors, assembly lines, and in workshops.

The DATA-KMU research project, jointly conducted by the TUM Chair for Strategy and Organization (Prof. Dr. Isabell Welpe) and IPRI gGmbH (Prof. Dr. Mischa Seiter), aims to close this gap. The project identifies what actually makes manufacturing SMEs attractive to blue-collar workers — both for recruitment and long-term retention — and translates these findings into a freely accessible, web-based IT tool (the "Arbeitgeberattraktivitäts-Kompass"). This tool will enable SMEs to benchmark their employer attractiveness, identify weaknesses, and implement tailored, evidence-based measures.

As a HiWi, you will be an active part of the research team. Your work will directly feed into the empirical foundation of the project — helping us understand what blue-collar workers truly value in an employer and how manufacturing SMEs can systematically improve their attractiveness.

🦾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 Agile Organisations and Digital Disruption, Blockchain Technology, Creativity and Innovation, Digital Transformation and Business Model Innovation, Diversity, Education: Education Technology and Performance Management, HRTech, Leadership, and Teams. We are always early in noticing trends, technologies, strategies, and organisations that shape the future, which has its ups and downs.

🎯 Goals

You will be able work in a team with multiple master thesis students and coordinate their work. The project tasks include:

• Interview & focus group coordination: Reach out to and schedule interviews and focus groups with SME representatives (HR managers, production leads, managing directors), blue-collar workers, vocational school students, and industry association representatives (IHK, HWK)
• Interview & focus group support: Conduct and document semi-structured interviews and focus group discussions (in German)
• Web scraping & data collection: Support the collection and structuring of data from job postings, career websites, and employer review platforms (e.g., Kununu, Glassdoor) using web scraping and text mining techniques
• Data analysis: Support qualitative and quantitative analysis of interview data, survey data, and web-scraped content, including coding, content analysis, and synthesis of key findings
• Conjoint analysis support: Assist in the design, programming, and evaluation of Adaptive Conjoint Analyses to identify and prioritize employer attractiveness factors
• General project support: Assist with literature research, preparation of project reports, workshop materials, and internal documentation

🎓 Profile

• Native or fluent German speaker (you will conduct interviews and focus groups in German)
• Completed Bachelor's degree (in management, psychology, industrial engineering, social sciences, information systems, or a related field)
• Interest in employer branding, skilled labor markets, HR strategy, and/or the manufacturing sector
• Willingness to engage with mixed-methods research (qualitative interviews, surveys, web scraping, conjoint analysis)
• Experience with or willingness to learn data collection tools (e.g., Python for web scraping, survey platforms) is a plus
• Reliable, structured, self-driven working style and ability to work independently

📝 How to Apply

If you are interested, please send a mail to Philipp Schaffer (philipp.schaffer@tum.de) with the subject line "DATA-KMU HiWi | Application [Your Name]" together with:

• Your CV
• Current transcript of records / grade report
• Preferred starting date
• A short motivation statement (why this topic, what relevant background do you bring)