9. September 2021

Beitrag veröffentlicht in der Zeitschrift Applied Science

Die Interview-basierte Studie mit dem Titel „Cooperative approaches to data sharing and analysis for industrial internet of things ecosystems" wurde zur Veröffentlichung in der Zeitschrift Applied Science angenommen. Autoren des Beitrags sind Dr. Henning Baars, Dr. Ann Tank, Patrick Weber, Prof. Dr. Hans-Georg Kemper, Prof. Dr. Heiner Lasi und Prof. Dr. Burkhard Pedell. Der Beitrag ist im Rahmen des Forschungsprojekts „Datengenossenschaften“ (www.datengenossenschaft.com) entstanden, an welchem der Lehrstuhl für Wirtschaftsinformatik 1 und der Lehrstuhl für Controlling des BWI beteiligt sind. Der Artikel ist unter nachfolgendem Link frei verfügbar: https://doi.org/10.3390/app11167547

Abstract des Beitrags:

The collection and analysis of industrial Internet of Things (IIoT) data offer numerous opportunities for value creation, particularly in manufacturing industries. For small and medium-sized enterprises (SMEs), many of those opportunities are inaccessible without cooperation across enterprise borders and the sharing of data, personnel, finances, and IT resources. In this study, we suggest so-called data cooperatives as a novel approach to such settings. A data cooperative is understood as a legal unit owned by an ecosystem of cooperating SMEs and founded for supporting the members of the cooperative. In a series of 22 interviews, we developed a concept for cooperative IIoT ecosystems that we evaluated in four workshops, and we are currently implementing an IIoT ecosystem for the coolant management of a manufacturing environment. We discuss our findings and compare our approach with alternatives and its suitability for the manufacturing domain.

Keywords: data sharing; industrial internet of things; business ecosystems; SME

Citation: Baars, Henning/Tank, Ann/Weber, Patrick/Kemper, Hans-Georg/Lasi, Heiner/Pedell, Burkhard (2021), Cooperative approaches to data sharing and analysis for industrial internet of things ecosystems, in: Applied Sciences, Vol. 11, 2021 (16), 7547, https://doi.org/10.3390/app11167547


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