Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/181583
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Campo DCValorIdioma
dc.contributor.advisorCastro, João-
dc.contributor.advisorRoth, Philipp-
dc.contributor.advisorFrei, Jen-
dc.contributor.authorMiranda, Laura Valentina Sanabria-
dc.date.accessioned2025-03-28T13:36:07Z-
dc.date.issued2025-01-23-
dc.date.submitted2024-12-17-
dc.identifier.urihttp://hdl.handle.net/10362/181583-
dc.description.abstractThis research paper analyzes the impact of a market-specific Retrieval Augmented Generation (RAG) model on public procurement in Switzerland. Despite the sector's developed transparency, it remains underutilized due to knowledge gaps and limited data accessibility. Therefore, this study explores how a customized RAG model can enhance data accessibility, automate processes, and strengthen analytical capabilities. Key areas of focus include automating repetitive tasks, ensuring compliance, integrating relevant APIs, and conducting analytics. Finally, the research outlines recommendations for developing RAG models and their potential to drive innovation in public procurement in Switzerland.pt_PT
dc.language.isoengpt_PT
dc.relationUID/ECO/00124/2013pt_PT
dc.rightsembargoedAccesspt_PT
dc.subjectRetrieval-Augmented Generation (RAG)pt_PT
dc.subjectChatbotpt_PT
dc.subjectPublic procurementpt_PT
dc.subjectE-Governmentpt_PT
dc.subjectSwitzerlandpt_PT
dc.subjectArtificial Intelligence (Ai)pt_PT
dc.subjectDigitalizationpt_PT
dc.titleInnovating public procurement: impact of a market-specific retrieval-augmented generation model for Switzerlandpt_PT
dc.typemasterThesispt_PT
thesis.degree.nameA Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economicspt_PT
dc.date.embargo2028-01-23-
dc.identifier.tid203927567pt_PT
dc.subject.fosDomínio/Área Científica::Ciências Sociais::Economia e Gestãopt_PT
Aparece nas colecções:NSBE: Nova SBE - MA Dissertations

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