Business model archetypes of open data intermediaries: Empirical insights from practice

Abstract Open data intermediaries are critical for enhancing value generation from open data. However, empirical research on their business model archetypes remains limited. This gap constrains our understanding of the conditions and potential innovations required to perform the roles of open data intermediaries sustainably. To address this gap, we developed a taxonomy and empirically derived business model archetypes based on 190 open data intermediaries. We identified nine archetypes: collaborative open data platforms, premium self-service data delivery, personalized open data services, interactive apps with other complementary products, open data repositories funded by sponsorship, one-stop packages around an (augmented) open data platform/repository, single-purpose apps, interactive apps without complementary products, and open data advocacy. We also described each archetype’s value proposition, value creation, and value capture dimensions. Our findings support further research into the conditions that contribute to the success of open data intermediaries’ business models and the design of new, innovative ones. They also provide business model inspiration for existing and potential open data intermediaries, thereby encouraging greater exploitation of open data value.