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Business Model Clustering: A network-based approach in the field of e-mobility services

Engel, Christian; Haude, Jan; Kühl, Niklas ORCID iD icon


Empirical insights about business models in the field of e-mobility services are of high importance to academia, industry and politics. As basic clustering algorithms do not deliver semantically valuable findings on business model structures based on obtained empiric data, this paper proposes a similarity measure-based network approach of clustering the latter. On the basis of graph, social network and similarity measure theory, an approach is designed which compares every business model instances of a data set with each other. The paper comes up with a matching score in order to determine whether two business models are connected contentwise within a cluster or not. The plotting of the resulting matching scores leads to a visually based determination of a meaningful matching score which bonds two business models together or not. The elaborations result in four e-mobility service clusters: Dataand-software-driven-, brokering-, transportation- and energy supply-based business models. Additionally, further findings on current opportunities in clustering business models and future solution proposals are described.

Volltext §
DOI: 10.5445/IR/1000076317
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Karlsruhe Service Research Institute (KSRI)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2017
Sprache Englisch
Identifikator ISSN: 2194-1629
KITopen-ID: 1000076320
Erschienen in Proceedings of the Second KSS Research Workshop : Karlsruhe, Germany, February 2016. Ed.: P. Hottum
Verlag Karlsruher Institut für Technologie (KIT)
Seiten 11-25
Serie KIT Scientific Working Papers ; 69
Schlagwörter Energy and Mobility Services, E-mobility, Business Models, Clustering
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