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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.respol.2004.07.010 Byline: Bart Verspagen, Claudia Werker Keywords: Scale-free networks; Scientific interaction; Evolutionary economics; Innovation studies Abstract: This paper uses a database on scientific interaction in the field of the economics of technological change and innovation. The database is used to address two issues. First, the network is shown to be (approximately) scale-free. This suggests that growth of the number of scholars active in the field and so-called preferential attachment (i.e., scholars entering the field prefer to attach themselves to highly reputable existing members of the network) are characteristic of the nature of the underlying field. Thus, increasing returns seem to govern mechanisms of reputation formation. Second, the potential existence of cohesive subgroups of relatively strongly connected scholars is explored, and the implications of this for the paradigmatic structure of the field are discussed. Author Affiliation: Eindhoven Centre for Innovation Studies (ECIS), Eindhoven University of Technology, Eindhoven 5600 MB, The Netherlands Article History: Received 18 March 2004; Revised 18 June 2004; Accepted 2 July 2004

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 marketplacearchetype. Consortium-owned data marketplaces apply the archetypes of aggregating data marketplace with additional brokering serviceand consulting data marketplace. Independently owned data marketplaces with market orientation apply the facilitating data marketplacearchetype. 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.