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

Frederik Möller (), Maleen Stachon, Can Azkan, Thorsten Schoormann and Boris Otto
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Frederik Möller: TU Dortmund University
Maleen Stachon: TU Dortmund University
Can Azkan: Fraunhofer ISST
Thorsten Schoormann: University of Hildesheim
Boris Otto: TU Dortmund University

Electronic Markets, 2022, vol. 32, issue 2, No 21, 726 pages

Abstract: 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.

Keywords: Taxonomy; Business model; Classification; Literature review; Business model taxonomy; A10 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s12525-021-00507-x

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