The goal of this paper is to demonstrate the feasibility of combining visualization and reasoning for business model design by combining the machine-interpretability of ontologies with a further development of the widely accepted business modeling tool, the Business Model Canvas (BMC). Since ontologies are a machine-interpretable representation of enterprise knowledge and thus, not very adequate for human interpretation, we present a tool that combines the graphical and human interpretable representation of BMC with a business model ontology. The tool connects a business model with reusable data and interoperability to other intelligent business information systems so that additional functionalities are made possible, such as a comparison between business models. This research follows the design science strategy with a qualitative approach by applying literature research, expert interviews, and desk research. The developed AOAME4BMC tool consists of the frontend, a graphical web-based representation of an enhanced BMC, a web service for the data exchange with the backend, and a specific ontology for the machine-interpretable representation of a business model. The results suggest that the developed tool AOAME4BMC supports the suitability of an ontology-based representation for business model design.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.