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Designing business model taxonomies – synthesis and guidance from information systems research

Author

Listed:
  • Frederik Möller

    (TU Dortmund University
    Fraunhofer ISST)

  • Maleen Stachon

    (TU Dortmund University)

  • Can Azkan

    (Fraunhofer ISST)

  • Thorsten Schoormann

    (University of Hildesheim)

  • Boris Otto

    (TU Dortmund University
    Fraunhofer ISST)

Abstract

Classification is an essential approach in business model research. Empirical classifications, termed taxonomies, are widespread in and beyond Information Systems (IS) and enjoy high popularity as both stand-alone artifacts and the foundation for further application. In this article, we focus on the study of empirical business model taxonomies for two reasons. Firstly, as these taxonomies serve as a tool to store empirical data about business models, we investigate their coverage of different industries and technologies. Secondly, as they are emerging artifacts in IS research, we aim to strengthen rigor in their design by illustrating essential design dimensions and characteristics. In doing this, we contribute to research and practice by synthesizing the diffusion of business model taxonomies that helps to draw on the available body of empirical knowledge and providing artifact-specific guidance for building taxonomies in the context of business models.

Suggested Citation

  • Frederik Möller & Maleen Stachon & Can Azkan & Thorsten Schoormann & Boris Otto, 2022. "Designing business model taxonomies – synthesis and guidance from information systems research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 701-726, June.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:2:d:10.1007_s12525-021-00507-x
    DOI: 10.1007/s12525-021-00507-x
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    Cited by:

    1. Simon Scheider & Florian Lauf & Simon Geller & Frederik Möller & Boris Otto, 2023. "Exploring design elements of personal data markets," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-16, December.
    2. Nora Nahr & Marikka Heikkilä, 2022. "Uncovering the identity of Electronic Markets research through text mining techniques," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1257-1277, September.
    3. Xiao Han & Jiayun Zhang, 2022. "Business Model Innovation Paths of Manufacturing Oriented towards Green Development in Digital Economy," IJERPH, MDPI, vol. 19(24), pages 1-34, December.

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