The topics offered for bachelor's and master’s theses are based on the research directions of the chair.  Our methodological focus includes:

• Data analytics methods (e.g., from machine learning, artificial intelligence)
• Heuristics
• Integration of data analytics methods into classical operations research methods to solve combinatorial optimization problems

Typical application areas include:

• Sustainable logistics and mobility systems
• Integration of new technologies or business models in logistics and mobility systems
• Energy management optimization in vertical farming systems
• Sustainable production planning systems

We welcome student-initiated topic proposals, provided they align with the chair’s research profile and meet methodological rigor.

The allocation of Bachelor’s and Master’s thesis students to the Chair of Business Administration, esp. Data Analytics, follows the centralized allocation procedure managed by the Mercator School of Management (MSM). Further information about the procedure, including deadlines and application requirements, can be found here.

Once the allocation process is completed, we will contact you directly to inform you whether you have been assigned to our chair for the respective semester. If so, a first introductory meeting will be scheduled to discuss potential thesis topics and your academic background.

Approximately 3–4 weeks after this introductory meeting, you are required to submit a thesis proposal (Exposé) to your assigned supervisor. The Exposé should be two pages long (bibliography excluded) and must include the following elements:

• Title of the thesis
• Description of the research topic
• Relevance and motivation of the study
• Identification of the research gap
• Clear research question(s) or objective(s)
• Proposed methodology
• Preliminary timeline for thesis execution
• Bibliography featuring at least three high-ranking peer-reviewed journal articles (e.g., VHB-JOURQUAL in the sections operations research, logistics, production, or business informatics)

After the Exposé has been submitted, a second meeting will be scheduled to discuss it in detail. Based on this feedback, you may revise your Exposé before final approval.

Once the Exposé has been approved, the thesis will be registered with the Examination Office. Registration must take place within the same semester in which you were assigned to the chair via the centralized allocation procedure. If you wish to start or register your thesis in a different semester, you must reapply through the central allocation process.

Formal Requirements

For both Bachelor’s and Master’s theses, we refer to the official MSM Thesis Guidelines (available here) for formatting, structure, citation standards, and submission procedures.

Methodological Requirements 

All the theses supervised by our chair must demonstrate a solid methodological foundation in data analytics and operations research. This includes:

• Understanding of machine learning and artificial intelligence methods
• Ability to formulate mathematical optimization models
• Familiarity with solution approaches, e.g., exact algorithms and metaheuristics

Master’s theses are expected to include software-based implementation (e.g., in Python or C++) of the proposed model and/or methodology.

Bachelor’s theses may be completed without full implementation, but must include a detailed manual application example (e.g., step-by-step solution of a small-scale instance).

Examination Colloquium 

After grading, all students are required to present their thesis in a mandatory examination colloquium organized by the chair. This presentation is an integral part of the assessment and contributes to the final grade.

• The centralized allocation procedure is mandatory for thesis assignment. No individual assignments are possible outside this process
• Late registration or rescheduling of the thesis requires re-entry into the allocation system
• Supervision is only granted to students who have completed the allocation process and are officially assigned to the chair