Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/228937
Authors: 
Bartsch, Devis
Winkler, Herwig
Year of Publication: 
2020
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29 [ISBN:] 978-3-7531-2346-2 [Year:] 2020 [Pages:] 699-735
Abstract: 
Purpose: Due to the large number of intermediaries in logistics networks there is avariety of possible failures, frictions and waste of time and money among the logisticsprocess chain. With the ability to provide data securely in near real-time, liketrack and tracing data of goods to every participant, the Blockchain-Technology(BCT) can help to solve these problems. Methodology: A structured literature analysis has been executed by using the databasesWeb of Science and Science Direct to find out current intermediary's functionsand real use cases. In addition, available other sources, like manufacturer websites,blog entries or whitepapers are searched for specific blockchain-based applicationsinvented and used by German companies. The identified use cases are then qualitativelyanalyzed. Findings: The first results showed that most of the business cases are still in the conceptphase or are merely ideas how the BCT could solve existing problems. Additionally,we got results on the distribution of applications and economic benefits alongthe logistics chain. Furthermore, important conclusions on implementation problemscan be derived from this. Originality: In order to maintain Germany's top economic position, it is necessaryto push ahead with the adaption of the BCT. Our analysis contains first results in thearea of real blockchain use cases of German companies. Initial comparisons betweencurrently used and blockchain-based logistics networks are also possible.
Subjects: 
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-sa/4.0/
Document Type: 
Conference Paper

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