Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.1472
DC FieldValueLanguage
dc.contributor.authorZrenner, Johannes-
dc.contributor.authorHassan, Ahmad Pajam-
dc.contributor.authorOtto, Boris-
dc.contributor.authorMarx Gómez, Jorge Carlos-
dc.contributor.editorKersten, Wolfgangde_DE
dc.contributor.editorBlecker, Thorstende_DE
dc.contributor.editorRingle, Christian M.de_DE
dc.date.accessioned2017-11-24T09:28:35Z-
dc.date.available2017-11-24T09:28:35Z-
dc.date.issued2017-10-
dc.identifier.citationDigitalization in supply chain management and logisticsde_DE
dc.identifier.isbn978-3-7450-4328-0de_DE
dc.identifier.issn2365-5070de_DE
dc.identifier.urihttp://tubdok.tub.tuhh.de/handle/11420/1475-
dc.description.abstractThe supply network structure of manufacturers is complex and non-transparent. In order to achieve a higher visibility and consequently increase the performance, the existing lack of data has to be closed. This paper answers the questions, how to identify, describe and compare suitable data sources for an end-to-end visibility. Following the design science research process, two artifacts are developed based on conceptual-to-empirical approaches. The initial conceptualizations result from literature reviews. The conceptual representation of supply network structure data sources clarifies the relevant data entities and attributes. It supports the identification process of relevant data sources. The data source taxonomy (i.e. classification scheme) describes data sources using fourteen dimensions and up to four potential characteristics. It assists a standardized description. Both artifacts are demonstrated in case studies with German automotive Original Equipment Manufacturers. The findings add to the knowledge base of supply network visibility with a focus on the network structure. A large part of the existing literature about supply chain visibility is too vague on the data perspective. Therefore, this paper closes an important gap regarding the supply chain digitalization by introducing two applicable results, which enable a new course of action for practitioners and researchers.en
dc.language.isoende_DE
dc.publisherepublide_DE
dc.relation.ispartofProceedings of the Hamburg International Conference of Logistics (HICL)de_DE
dc.relation.ispartofseriesProceedings of the Hamburg International Conference of Logistics (HICL);23-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.subjectdata source taxonomyde_DE
dc.subjectsupply chain visibilityde_DE
dc.subjectsupply network structurede_DE
dc.subjectdesign science researchde_DE
dc.subject.ddc330: Wirtschaftde_DE
dc.titleData source taxonomy for supply network structure visibilityde_DE
dc.typeinProceedingsde_DE
dc.identifier.urnurn:nbn:de:gbv:830-88217690-
dc.identifier.doi10.15480/882.1472-
dc.type.dinicontributionToPeriodical-
dc.subject.ddccode330-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-88217690de_DE
tuhh.oai.showtrue-
dc.identifier.hdl11420/1475-
tuhh.abstract.englishThe supply network structure of manufacturers is complex and non-transparent. In order to achieve a higher visibility and consequently increase the performance, the existing lack of data has to be closed. This paper answers the questions, how to identify, describe and compare suitable data sources for an end-to-end visibility. Following the design science research process, two artifacts are developed based on conceptual-to-empirical approaches. The initial conceptualizations result from literature reviews. The conceptual representation of supply network structure data sources clarifies the relevant data entities and attributes. It supports the identification process of relevant data sources. The data source taxonomy (i.e. classification scheme) describes data sources using fourteen dimensions and up to four potential characteristics. It assists a standardized description. Both artifacts are demonstrated in case studies with German automotive Original Equipment Manufacturers. The findings add to the knowledge base of supply network visibility with a focus on the network structure. A large part of the existing literature about supply chain visibility is too vague on the data perspective. Therefore, this paper closes an important gap regarding the supply chain digitalization by introducing two applicable results, which enable a new course of action for practitioners and researchers.de_DE
tuhh.publisher.urlhttps://www.epubli.de/shop/buch/2000000069144-
tuhh.identifier.doi10.15480/882.1472-
tuhh.type.opusInProceedings (Aufsatz / Paper einer Konferenz etc.)de
tuhh.gvk.hasppnfalse-
tuhh.hasurnfalse-
tuhh.series.id15de_DE
tuhh.series.nameProceedings of the Hamburg International Conference of Logistics (HICL)-
openaire.rightsinfo:eu-repo/semantics/openAccessde_DE
dc.type.drivercontributionToPeriodical-
dc.rights.ccby-sade_DE
dc.rights.ccversion4.0de_DE
dc.type.casraiConference Paperen
tuhh.container.startpage117de_DE
tuhh.container.endpage137de_DE
dc.relation.conferenceHamburg International Conference of Logistics (HICL) 2017de_DE
tuhh.relation.ispartofseriesnumber23de_DE
item.fulltextWith Fulltext-
item.creatorOrcidZrenner, Johannes-
item.creatorOrcidHassan, Ahmad Pajam-
item.creatorOrcidOtto, Boris-
item.creatorOrcidMarx Gómez, Jorge Carlos-
item.grantfulltextopen-
item.languageiso639-1other-
item.creatorGNDZrenner, Johannes-
item.creatorGNDHassan, Ahmad Pajam-
item.creatorGNDOtto, Boris-
item.creatorGNDMarx Gómez, Jorge Carlos-
crisitem.author.orcid0000-0003-3189-9461-
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