Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/228917
Authors: 
Brylowski, Martin
Ludwig, Maximilian
Kersten, Wolfgang
Schultze, Wolfgang
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:] 25-76
Abstract: 
Purpose: Product modularization and supply chain integration have establishedthemselves as efficient methods for complexity management, but a holistic view oftheir effects has rarely been studied. For this reason, we demonstrate a conceptwhich presents these effects along the product life-cycle phases (PLCP) and the strategicsuccess factor (SSF): Methodology: We applied a systematic literature review and carried out 13 semistructuredexpert interviews to cover the perspective of science as well as practice.Using qualitative content analysis, the effects of product modularization in integratedsupply chains is elaborated. The effects were allocated to the appropriate PLCP and subsequently assigned to the affected SSF. Findings: We found positive and negative modularization effects in each phase of theproduct life-cycle: development, procurement, production, sales, and after-sales.Within the appropriate PLCP, the effects were allocated to the SSF: cost, time, quality,flexibility, and risk. Scientists as well as practitioners are aware of the positiveeffects of modularization. Negative effects are largely neglected in both perspectives. Originality: The developed concept provides a holistic view of product modularizationeffects under consideration of an integrated supply chain. Besides the PLCP specificeffects are assigned to the affected SSF. This enables a structured and categorizedassessment of modularization effects in integrated supply chains and revealshidden as well as undesirable side effects for science and practice.
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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