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Overcoming Inefficiency in Public Procurement: An OpenData Approach

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dc.contributor.authorKlassen, Gerhard
dc.contributor.authorPalombo, Raphael
dc.contributor.authorBauer, Luca T.
dc.contributor.authorNiehaves, Björn
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorWohlgemuth, Volker
dc.date.accessioned2023-11-29T14:50:19Z
dc.date.available2023-11-29T14:50:19Z
dc.date.issued2023
dc.description.abstractThis paper discusses the need for an OpenData platform with data-based services to ad- dress the challenges facing the public procurement market. In the last 15 years, public procurement has doubled and now accounts for 15% of GDP. However, there is a shortage of skilled workers, and many tenders are still created manually. By leveraging advanced technologies such as machine learning and predictive analytics, we aim to improve the efficiency and effectiveness of public pro- curement. Our paper highlights the urgent need for a data-driven approach to public procurement and presents our plans for an OpenData platform that can deliver significant benefits to both the public sector and private enterprises.en
dc.identifier.doi10.18420/inf2023_121
dc.identifier.isbn978-3-88579-731-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43043
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2023 - Designing Futures: Zukünfte gestalten
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-337
dc.subjectOpenData
dc.subjectProcurement
dc.subjectMachine Learning
dc.subjectArtificial Intelligence
dc.titleOvercoming Inefficiency in Public Procurement: An OpenData Approachen
dc.typeText/Conference Paper
gi.citation.endPage1102
gi.citation.publisherPlaceBonn
gi.citation.startPage1097
gi.conference.date26.-29. September 2023
gi.conference.locationBerlin
gi.conference.sessiontitleÖffentliche Infrastruktur - Interoperabilität und Standardisierung der digitalen öffentlichen Beschaffung

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P337 - INFORMATIK 2023 - Designing Futures: Zukünfte gestalten