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.

政策制定者和分析师正在大力推广数据市场，以促进公司之间的数据交易。现有的商业模式文献涵盖了个人拥有的多边数据市场。然而，这些特定类型的数据市场几乎无法进行商业开发。本文为所有数据市场类型开发了商业模型原型，从私有所有权到独立所有权，从分层到市场导向。通过探索性访谈和案例分析，我们创建了一个商业模式分类法。我们的分类模式揭示了四种商业模式原型。我们发现具有分层导向的私有数据市场应用聚合数据市场原型。联盟拥有的数据市场应用原型通过额外的代理服务和咨询数据市场聚合数据市场。以市场为导向的独立拥有的数据市场应用促进数据市场原型。我们的结果为解释数据市场业务模型性能的配置理论提供了基础。我们的结果还为指定数据市场业务模型理论的边界条件提供了基础，例如，网络效应的重要性在原型之间存在很大差异。