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Institute of Business Informatics – Information Engineering
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Scientific Theses.

Information about Bachelor's, Master's and, if applicable, PhD dissertations including proposed topics

Students will only be supervised for their final theses provided they are assigned to the corresponding courses. In addition to the topics listed here, students and interested business partners can also approach our academic faculty team with suggestions for their own topics.

The general process involved in supervising Bachelor's or Master's theses:

  • Attendance in the corresponding course is mandatory
  • Supervision is approved based on the available resources and the selected topic - topics of a purely technical nature are unlikely to receive supervision
  • Students must hold a minimum of two presentations as part of the course: a proposal or interim presentation, and a final presentation.
  • Grading is not only based on the submitted assignments, but also the entire process as well as the presentations
  • All of the assignments/papers submitted for grading will be subject to a plagiarism review
  • Using artificial intelligence (AI) to produce thesis content is strictly prohibited
  • If using AI to, for example, improve the paper's writing style, you must discuss this in advance with your supervisor and state the information explicitly in your paper

Additional information regarding the course and how to communicate effectively with supervisors will be sent either directly by e-mail or be available in Moodle to students enrolled in the course.

The following topics are also the focus of the institute's research:

  • Antecedents of digitalization strategies in organizations
  • Benchmarking of digitalization strategies and programs
  • Success factors of implementing digitalization strategies in organizations
  • Open strategic IT planning, information requirements for strategic IT planning and use of forecast markets
  • CIO Roles, Strategies and Success

  • Methodology to conduct longitudinal studies in IT governance and strategic information management
  • Methods and metrics for direct and indirect success evaluation of software products
  • Methods for characterizing software ecosystems and platforms as well as their evolution
  • Data envelopment analysis (DEA) as a method in information management