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dc.contributor.authorBarrientos-Aguilar, A.es_PE
dc.contributor.authorGamboa-Cruzado, J.es_PE
dc.contributor.authorLópez-De-Montoya, R.L.es_PE
dc.contributor.authorCéliz, N.M.O.es_PE
dc.contributor.authorHuaman, L.A.es_PE
dc.contributor.authorSinche Crispin, F.S.es_PE
dc.contributor.authorRíos-Toledo, G.es_PE
dc.date.accessioned2026-02-25T17:44:23Z
dc.date.available2026-02-25T17:44:23Z
dc.date.issued2025
dc.identifier.urihttp://hdl.handle.net/20.500.14074/9904
dc.description.abstractFreight transport by road plays a crucial role in the economy of any nation by enabling the efficient distribution of materials and goods across its territory. However, this sector has faced challenges in decision-making, driving companies to explore methods that optimize this process through effective information management. This research aims to implement Business Intelligence (BI) to optimize freight transport and analyze its impact on improving operational efficiency and service quality. The study was based on a sample of 30 freight transport processes, individually evaluated to determine relevant indicators. To achieve this, the Hefesto methodology was applied, complemented by the development of dashboards using Power BI. The results showed a significant improvement in delivery punctuality, optimized distribution times, and increased customer satisfaction. Additionally, it is recommended that future research incorporate predictive models or data mining techniques to enhance analysis and decision-making.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherInstituto Politecnico Nacional.es_PE
dc.relation.ispartofhttps://www.scopus.com/pages/publications/105003642154es_PE
dc.relation.ispartofurn:issn:14055546es_PE
dc.relation.ispartofComput. Sist. 2025; 29(1): 511 - 528es_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/es_PE
dc.subjectBusiness intelligencees_PE
dc.subjectHefestoes_PE
dc.subjectfreight transportes_PE
dc.subjectOLTPes_PE
dc.subjectETLes_PE
dc.subjectpower BIes_PE
dc.titleTransforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector.es_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.02es_PE
dc.identifier.doihttps://doi.org/10.13053/cys-29-1-5544es_PE


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