The continuous innovation of its business models is an important task for a company to stay competitive. During this process, the company has to validate various hypotheses about its business models by adapting to uncertain and changing customer needs. To represent business models for idea generation, the Business Model Canvas  is mostly used. In the past, we have used the concept of feature models to represent the variability of a business model . The goal of this thesis is to conceptualize and implement a tool in Angular, which can (1) mine a feature model out of a set of existing business models, (2) derive new business models from the feature model, (3) learn validated and disapproved business decisions (see Figure 1). To do this standard-techniques like Feature Model Mining  or Questionnaire-based Variability Modeling  can be applied to the new context of business models.
- Literature Review on Business Models & Feature Models
- Conception and Design of the Algorithms and the Tool
- Implementation of the Algorithms and the Tool in Angular
- Evaluation in a Case Study
-  Osterwalder et al.: Business Model Generation (2010)
-  Gottschalk et al.: Intertwined Development of Business Model and Product Functions: A Twin Peak Feature Modeling Approach (2019)
-  She: Feature Model Mining (2008)
-  La Rosa et al.: Questionare-based Variability Modeling for System Configuration (2008)
The topic can be taken as a bachelor- or master thesis. It is possible to write this thesis in German or English. The requirements for the topic are passed courses of Data Mining (bachelor) or Machine Learning I (master). Please write in your application shortly why you are interested in the topic and what further experience you have in the field. Before the proposal process, there will be a short test (consisting of general questions, your understanding of the topic and a small programming task) to see if you are the right person for the topic.