Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/228920 
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 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2020 [Pages:] 153-185
Publisher: 
epubli GmbH, Berlin
Abstract: 
Purpose: Supply chain networks face an increasing demand to integrate globally distributedcustomers and suppliers. As supply chain processes are deemed to lack sufficienttransparency and security, blockchain solutions are piloted to offer an IT infrastructurecovering these needs. This paper aims to bring current projects one stepfurther and evolves a model for integrating blockchain solutions into supply chainprocesses. Methodology: In order to get an overview of existing models for technology integration,an exploratory research study is conducted. In addition, requirements for thespecific integration of blockchain solutions are gathered and categorized in a systematiccontent analysis. Based on these requirements, the models are evaluated,compared and utilized for the development of a new model. Findings: Since none of the presented models fully meet the specific blockchainbasedrequirements, the existing models must be further developed. Specifically, increasesin the number of supply chain partners and external stakeholders involvedin blockchain-based systems are not supported by current models, and need to beintegrated systematically. Originality: In this paper, an integration model is developed that is particularly suitablefor blockchain integration into supply chain processes. In order to give startingpoints for a validation of the model, a case study is conducted in the field of blockchain-based payment gateway solutions.
Subjects: 
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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