Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector.
Descripción del Articulo
Freight 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 effect...
| Autores: | , , , , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2025 |
| Institución: | Universidad Nacional de Cajamarca |
| Repositorio: | UNC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.unc.edu.pe:20.500.14074/9904 |
| Enlace del recurso: | http://hdl.handle.net/20.500.14074/9904 https://doi.org/10.13053/cys-29-1-5544 |
| Nivel de acceso: | acceso abierto |
| Materia: | Business intelligence Hefesto freight transport OLTP ETL power BI https://purl.org/pe-repo/ocde/ford#1.02.02 |
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Barrientos-Aguilar, A.Gamboa-Cruzado, J.López-De-Montoya, R.L.Céliz, N.M.O.Huaman, L.A.Sinche Crispin, F.S.Ríos-Toledo, G.2026-02-25T17:44:23Z2026-02-25T17:44:23Z2025http://hdl.handle.net/20.500.14074/9904https://doi.org/10.13053/cys-29-1-5544Freight 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.application/pdfengInstituto Politecnico Nacional.https://www.scopus.com/pages/publications/105003642154urn:issn:14055546Comput. Sist. 2025; 29(1): 511 - 528info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Business intelligenceHefestofreight transportOLTPETLpower BIhttps://purl.org/pe-repo/ocde/ford#1.02.02Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector.info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:UNC-Institucionalinstname:Universidad Nacional de Cajamarcainstacron:UNCORIGINAL2007-9737-cys-29-01-511.pdf2007-9737-cys-29-01-511.pdfapplication/pdf1255351http://repositorio.unc.edu.pe/bitstream/20.500.14074/9904/1/2007-9737-cys-29-01-511.pdfe16b11d6b2984a98149c4866e2a19f0aMD5120.500.14074/9904oai:repositorio.unc.edu.pe:20.500.14074/99042026-02-26 11:05:38.223Universidad Nacional de Cajamarcarepositorio@unc.edu.pe |
| dc.title.es_PE.fl_str_mv |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| title |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| spellingShingle |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. Barrientos-Aguilar, A. Business intelligence Hefesto freight transport OLTP ETL power BI https://purl.org/pe-repo/ocde/ford#1.02.02 |
| title_short |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| title_full |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| title_fullStr |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| title_full_unstemmed |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| title_sort |
Transforming Freight Transport with Business Intelligence: A Case Study in the Peruvian Logistics Sector. |
| author |
Barrientos-Aguilar, A. |
| author_facet |
Barrientos-Aguilar, A. Gamboa-Cruzado, J. López-De-Montoya, R.L. Céliz, N.M.O. Huaman, L.A. Sinche Crispin, F.S. Ríos-Toledo, G. |
| author_role |
author |
| author2 |
Gamboa-Cruzado, J. López-De-Montoya, R.L. Céliz, N.M.O. Huaman, L.A. Sinche Crispin, F.S. Ríos-Toledo, G. |
| author2_role |
author author author author author author |
| dc.contributor.author.fl_str_mv |
Barrientos-Aguilar, A. Gamboa-Cruzado, J. López-De-Montoya, R.L. Céliz, N.M.O. Huaman, L.A. Sinche Crispin, F.S. Ríos-Toledo, G. |
| dc.subject.es_PE.fl_str_mv |
Business intelligence Hefesto freight transport OLTP ETL power BI |
| topic |
Business intelligence Hefesto freight transport OLTP ETL power BI https://purl.org/pe-repo/ocde/ford#1.02.02 |
| dc.subject.ocde.es_PE.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#1.02.02 |
| description |
Freight 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. |
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2025 |
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2026-02-25T17:44:23Z |
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2026-02-25T17:44:23Z |
| dc.date.issued.fl_str_mv |
2025 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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article |
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http://hdl.handle.net/20.500.14074/9904 |
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https://doi.org/10.13053/cys-29-1-5544 |
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http://hdl.handle.net/20.500.14074/9904 https://doi.org/10.13053/cys-29-1-5544 |
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eng |
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eng |
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https://www.scopus.com/pages/publications/105003642154 urn:issn:14055546 Comput. Sist. 2025; 29(1): 511 - 528 |
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info:eu-repo/semantics/openAccess |
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Instituto Politecnico Nacional. |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).