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Agent-based Models as a Method to Analyse Privacy-friendly Business Models in an Assistant Ecosystem

: Kubach, Michael; Fähnrich, Nicolas; Mihale-Wilson, Cristina

Volltext urn:nbn:de:0011-n-6154354 (473 KByte PDF)
MD5 Fingerprint: 6efd1f9caced7f19777b934a62ea9154
(CC) by-sa
Erstellt am: 26.11.2020

Roßnagel, Heiko (Hrsg.); Schunck, Christian H. (Hrsg.); Mödersheim, Sebastian (Hrsg.); Hühnlein, Detlef (Hrsg.) ; Gesellschaft für Informatik -GI-, Bonn; Gesellschaft für Informatik -GI-, Fachgruppe Biometrie und elektronische Signaturen -BIOSIG-:
Open Identity Summit 2020 : May 26th and 27th, 2020, Lyngby, Denmark
Bonn: GI, 2020 (GI-Edition - Lecture Notes in Informatics (LNI). Proceedings P-305)
ISBN: 978-3-88579-699-2
Open Identity Summit <2020, Lyngby/cancelled>
Bundesministerium fur Wirtschaft und Energie BMWi (Deutschland)
01MD16009D; ENTOURAGE - Smart Assistance
Enabling Trusted Ubiquitous Assistance
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAO ()

Various projects and initiatives strive towards designing privacy friendly open platforms and ecosystems for digital products and services. However, besides mastering technical challenges, achieving economic viability and broad market success has so far proven to be difficult for these initiatives. Based on a publicly funded research project, this study focuses on the business model design for an open digital ecosystem for privacy friendly and trustworthy intelligent assistants. We present how the agent-based modelling technique can be employed to evaluate how business models perform in various constellations of an open digital ecosystem. Thus, our work relates to the strategic choice of suitable business models as an important success factor for privacy and security-relevant technologies.