@inproceedings{21727,
  abstract     = {{Platform-based business models underlie the success of many of today’s largest, fastest-growing, and most disruptive companies. Despite the success of prominent examples, such as Uber and Airbnb, creating a profitable platform ecosystem presents a key challenge for many companies across all industries. Although research provides knowledge about platforms’ different value drivers (e.g., network effects), companies that seek to transform their current business model into a platform-based one lack an artifact to reduce knowledge boundaries, collaborate effectively, and cope with the complexities and dynamics of platform ecosystems. We address this challenge by developing two artifacts and combining research from variability modeling, business model dependencies, and system dynamics. This paper presents a design science research approach to develop the platform ecosystem modeling language and the platform ecosystem development tool that support researcher and practitioner by visualizing and simulating platform ecosystems. }},
  author       = {{Vorbohle, Christian and Gottschalk, Sebastian}},
  booktitle    = {{Proceedings of the 29th European Conference on Information Systems (ECIS)}},
  keywords     = {{Platform Ecosystems, Platform Ecosystem Modeling Language, Platform Ecosystem Development Tool, Business Models, Design Science}},
  location     = {{Virtual Conference/Workshop}},
  publisher    = {{AIS}},
  title        = {{{Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems }}},
  year         = {{2021}},
}

@inproceedings{9275,
  abstract     = {{In the last years, store-oriented software ecosystems are gaining
more and more attention from a business perspective. In these ecosystems,
third-party developers upload extensions to a store which can be
downloaded by end users. While the functional scope of such ecosystems
is relatively similar, the underlying business models differ greatly in and
between their different product domains (e.g. Mobile Phone, Smart TV).
This variability, in turn, makes it challenging for store providers to 
find a business model that fits their own needs.
To handle this variability, we introduce the Business Variability Model
(BVM) for modeling business model decisions. The basis of these decisions
is the analysis of 60 store-oriented software ecosystems in eight
different product domains. We map their business model decisions to the
Business Model Canvas, condense them to a variability model and discuss
particular variants and their dependencies. Our work provides store
providers a new approach for modeling business model decisions together
with insights of existing business models. This, in turn, supports them
in creating new and improving existing business models.}},
  author       = {{Gottschalk, Sebastian and Rittmeier, Florian and Engels, Gregor}},
  booktitle    = {{Business Modeling and Software Design}},
  editor       = {{Shishkov, Boris}},
  keywords     = {{Software Ecosystems, Business Models, Variabilities}},
  location     = {{Lisbon}},
  pages        = {{153--169}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Business Models of Store-Oriented Software Ecosystems: A Variability Modeling Approach}}},
  doi          = {{10.1007/978-3-030-24854-3_10}},
  year         = {{2019}},
}