The development of new and innovative business models is a central challenge for many companies, particularly for small and medium-sized companies. Information systems could support these companies by actively guiding them through a business model development process. However, the existing business model development tools only provide passive support for their users (e.g., digital whiteboards). Therefore, we set out to develop a prototype that actively supports its users by generating business model ideas. Informed by an existing design theory, we built a prototype relying on hybrid intelligence (i.e., the combination of human and artificial knowledge). The prototype iteratively generates new business model ideas by recombining existing knowledge, posts the ideas to a crowdsourcing platform for evaluation, and learns from the crowds’ evaluation. This demonstration paper presents the prototype, the challenges we faced during its implementation, and directions for future research on machine-supported business model development.
Klippenstein, Arthur; Weskamp, Dr. Christoph; Laux, Florian; Neuhaus, Florian; Pfannschmidt, Karlson; Bülling, Melissa; and Kassanke, Dr. Stephan, "A Prototype to Support Business Model Innovation through Crowdsourcing and Artificial Intelligence" (2023). Wirtschaftsinformatik 2023 Proceedings. 47.