Big Data and its Applications in Supply Chain Management: Findings from a Delphi Study

dc.contributor.author Brinch, Morten
dc.contributor.author Stentoft, Jan
dc.contributor.author Jensen, Jesper Kronborg
dc.date.accessioned 2016-12-29T00:34:42Z
dc.date.available 2016-12-29T00:34:42Z
dc.date.issued 2017-01-04
dc.description.abstract Big data and its applications have increasingly received interest by both scholars and practitioners. However, there is still missing evidence regarding how big data is understood as well as its applications in supply chain management (SCM). Empirical contributions are especially limited. This study seeks to address this gap through an explorative Delphi study to understand the terminology of big data and its application in the SCM processes of sourcing, manufacturing, service, logistics, planning, and return. The findings reveal that big data is mostly concerned with data collection and logistics, service, and planning processes are the most applicable processes for deploying big data analytics in SCM. Furthermore, a range of applications have been identified and ranked within each process.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2017.161
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41314
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Analytic applications
dc.subject Big data
dc.subject Delphi study
dc.subject SCOR
dc.subject Supply chain management
dc.title Big Data and its Applications in Supply Chain Management: Findings from a Delphi Study
dc.type Conference Paper
dc.type.dcmi Text
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