Methods, Modeling and Theories in the Field of Business Informatics
In the topic line of
Methods, modelling and theories of information systems
we offer topics for analysis, design, implementation, and evaluation in the following areas for a bachelor's, master's, diploma, or seminar thesis:
- Conceptual modeling (esp. domain-specific adaptation of modeling languages and optimization of graphical notation; secondary notation)
- Evolution of design artifacts
- Understanding of methods in WI
Evolution of IT Artefacts
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Design Science projects aim to design and evaluate IT artifacts (software, hardware, etc.). While some IT artifacts are created from scratch, most IT artifacts build on each other by evolving on the basis of existing artifacts. In this sense, these artifacts are evolving based on old artifacts. The Digital Health research group has developed a framework on this topic to help design researchers and practitioners describe the evolution of their artifacts (see the following publication). The thesis could focus, in particular, on the description of evolution processes for complex evolutions such as that of UML or BPMN. Another aspect of a research study (thesis) would be the investigation of how a repository could be designed to enable the management of evolutionary processes (in the broadest sense, an evolutionary database). This includes both design-oriented questions on method design and platform implementation, as well as evolutionary assignments on the context of use and acceptance of use. |
Reference process models
| Reference process models are central to process optimization and standardization in various industries. They offer proven templates for designing efficient and high-quality processes. Despite their potential, many different models have been developed and applied in different sectors. A systematic analysis of these reference process models is necessary to identify their mechanisms, success factors, and challenges and evaluate their actual use and effectiveness. This thesis could be designed as a systematic review that analyzes the existing literature on reference process models in different contexts. The focus is on identifying the mechanisms that contribute to increased efficiency and standardization and evaluating the factors that influence the use of reference process models in practice. |
Conceptual Modeling
| Conceptual Modeling and the Use of Large Language Models | |
|---|---|
| With the possibilities of Generative Large Language Models (LLM) such as those realized by GPT, trend-setting questions about potential applications in the area of domain conceptual modeling are also moving into the focus of business informatics research. In recent decades, domain conceptual modeling has established itself as an important tool in designing and managing information systems. However, research also shows that due to the complexity of integrated model systems and the tension between domain and methodological expertise, model creation and maintenance of the model system can be very challenging from an economic and technical point of view. Large language models are able to link domain knowledge and generate corresponding proposals for model creation and maintenance, as well as for the design and adaptation of modeling languages. The thesis should investigate these potential applications and design and evaluate solution approaches. Both overview theses and technically focused theses are of interest. | |
| Development of conceptual modeling through the potential of artificial intelligence |
| The integration of artificial intelligence poses new challenges for conceptual modeling. While AI systems are often data-driven, conceptual models are based on rules and abstraction. This topic investigates how data-driven and rule-based approaches can be combined to make AI decisions more explainable and transparent. One focus is on automating model generation using AI and ensuring model quality. Research is also being conducted into how models can be dynamically adapted to changing data. The explainability and transparency of AI and the management of models in the development process are key aspects. |
Application and design of AI-based diagnostic decision support systems
| The integration of AI-based assistance systems in the medical field is gaining increasing importance. Some of these systems have already reached market maturity and are being utilized in clinical practice. These systems offer diverse potential benefits, such as improved diagnostic accuracy and increased efficiency in healthcare delivery. However, they also pose challenges, such as the growing dependence of medical professionals on these technologies. To understand current developments and future potentials, it is essential to provide an overview of both the research landscape and practical applications. The focus should be on advancements in the field of diagnostic support systems, addressing questions related to the types of assistance systems, prevailing design approaches, key driving factors studied in research, and the precursors of AI-based diagnostic support systems. |
Use and design of maturity models in the healthcare sector
| Maturity Model Structures and Approaches |
| Maturity models are widely used in software development, IT management, and project management in various industries. They help organizations continuously measure and improve their efficiency and quality. Such a model usually consists of several maturity levels, ranging from a chaotic initial state to an optimized and fully mature state. This thesis aims to map the current landscape regarding the design, development, and application of maturity models, identify similarities and differences between existing approaches, and thus analyze the current state of the art in science and practice. |
| Maturity Model Designer |
| Based on an analysis of the current state of the art in research and practice related to maturity models, this work focuses on designing and developing a universal tool for creating and managing maturity models across various application scenarios. This includes defining structural elements (e.g., dimensions, maturity levels, evaluation criteria) as well as providing model definitions via a universal application programming interface (API). |
If you are interested, please e-mail a brief presentation of your ideas or subject interests, including your CV, to .