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On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks

J. Cirullies, C. Schwede, in: Proceedings of the 54th Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, 2021.

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Konferenzbeitrag | Veröffentlicht | Englisch
Autor*in
Cirullies, Jan; Schwede, ChristianFH Bielefeld
Abstract
Industrial companies already apply digital twins for the digital representation of the physical world. In addition, information sharing becomes increasingly decisive for the competition, e.g. in supply networks where products and logistics data such as demands and capacities are exchanged. As many companies are, however, highly reluctant to share data across the supply chain, this paper applies the methodology of design science research to, first, state the requirements for shared digital twins based on five industrial use cases. It turns out that with regard to data decentralism, sovereignty and compatibility through global standardization are key success factors. Hence, second, this paper presents a concept for a shared digital twin providing data on demand, i.e. at the right time and in particular with data condensed to the concrete need.
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Titel des Konferenzbandes
Proceedings of the 54th Hawaii International Conference on System Sciences
Konferenz
Hawaii International Conference on System Sciences
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Cirullies, Jan ; Schwede, Christian: On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks. In: Proceedings of the 54th Hawaii International Conference on System Sciences, Proceedings of the Annual Hawaii International Conference on System Sciences : Hawaii International Conference on System Sciences, 2021
Cirullies J, Schwede C. On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks. In: Proceedings of the 54th Hawaii International Conference on System Sciences. Proceedings of the Annual Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences; 2021. doi:10.24251/HICSS.2021.202
Cirullies, J., & Schwede, C. (2021). On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks. In Proceedings of the 54th Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2021.202
@inproceedings{Cirullies_Schwede_2021, series={Proceedings of the Annual Hawaii International Conference on System Sciences}, title={On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks}, DOI={10.24251/HICSS.2021.202}, booktitle={Proceedings of the 54th Hawaii International Conference on System Sciences}, publisher={Hawaii International Conference on System Sciences}, author={Cirullies, Jan and Schwede, Christian}, year={2021}, collection={Proceedings of the Annual Hawaii International Conference on System Sciences} }
Cirullies, Jan, and Christian Schwede. “On-Demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks.” In Proceedings of the 54th Hawaii International Conference on System Sciences. Proceedings of the Annual Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2021. https://doi.org/10.24251/HICSS.2021.202.
J. Cirullies and C. Schwede, “On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks,” in Proceedings of the 54th Hawaii International Conference on System Sciences, 2021.
Cirullies, Jan, and Christian Schwede. “On-Demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks.” Proceedings of the 54th Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences, 2021, doi:10.24251/HICSS.2021.202.
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2023-12-20T15:48:31Z


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