Print Email Facebook Twitter Business model archetypes for data marketplaces in the automotive industry Title Business model archetypes for data marketplaces in the automotive industry: Contrasting business models of data marketplaces with varying ownership and orientation structures Author Bergman, R. (Student TU Delft) Abbas, A.E. (TU Delft Information and Communication Technology) Jung, Sven (University of St. Gallen) Werker, C. (TU Delft Economics of Technology and Innovation) de Reuver, Mark (TU Delft Information and Communication Technology) Date 2022 Abstract Policymakers and analysts are heavily promoting data marketplaces to foster data trading between companies. Existing business model literature covers individually owned, multilateral data marketplaces. However, these particular types of data marketplaces hardly reach commercial exploitation. This paper develops business model archetypes for the full array of data marketplace types, ranging from private to independent ownership and from a hierarchical to a market orientation. Through exploratory interviews and case analyses, we create a business model taxonomy. Patterns in our taxonomy reveal four business model archetypes. We find that privately-owned data marketplaces with hierarchical orientation apply the aggregating data marketplace archetype. Consortium-owned data marketplaces apply the archetypes of aggregating data marketplace with additional brokering service and consulting data marketplace. Independently owned data marketplaces with market orientation apply the facilitating data marketplace archetype. Our results provide a basis for configurational theory that explains the performance of data marketplace business models. Our results also provide a basis for specifying boundary conditions for theory on data marketplace business models, as, for instance, the importance of network effects differs strongly between the archetypes. Subject Business data sharingData economyData marketsBusiness modelsTaxonomyArchetypes To reference this document use: http://resolver.tudelft.nl/uuid:03bd27a6-e6db-4b19-92a3-c9cb071a5bc3 DOI https://doi.org/10.1007/s12525-022-00547-x ISSN 1019-6781 Source Electronic Markets, 32 (2), 747-765 Part of collection Institutional Repository Document type journal article Rights © 2022 R. Bergman, A.E. Abbas, Sven Jung, C. Werker, Mark de Reuver Files PDF s12525_022_00547_x.pdf 2 MB Close viewer /islandora/object/uuid%3A03bd27a6-e6db-4b19-92a3-c9cb071a5bc3/datastream/OBJ/view