Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12394/16957
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dc.contributor.advisorCastañeda Vargas, Pedro Segundoes_PE
dc.contributor.authorCampos Contreras, Marco Antonioes_PE
dc.contributor.authorPalomino Jaime, Cristian Andreses_PE
dc.contributor.authorPantoja Vega, Jean Carloses_PE
dc.contributor.authorCajachagua Guerreros, Diegoes_PE
dc.contributor.authorCastañeda Vargas, Pedro Segundoes_PE
dc.date.accessioned2025-03-27T20:46:50Z-
dc.date.available2025-03-27T20:46:50Z-
dc.date.issued2024-
dc.identifier.citationCampos, M., Palomino, C., Pantoja, J., Cajachagua, D. y Castañeda, P. (2024). Technological Model Based on Big Data for Good Supply Chain Management in Agribusinesses. Tesis para optar por el título profesional de Ingeniero Empresarial, Escuela Académico Profesional de Ingeniería Empresarial, Universidad Continental, Huancayo, Perú.es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12394/16957-
dc.description.abstractAgribusiness is important to the global economy, but poor supply chain management can lead to losses and reduced customer satisfaction, which is why big data offers an opportunity to improve supply chain management in these sectors through big data-based technology models that focus on capturing, storing and analyzing big data to improve decision making in supply chain management. This big data improves communication and collaboration between the various players in the supply chain, resulting in better coordination and faster response to changing business requirements. Using real-time data and machine learning algorithms that can make better decisions and increase production and delivery efficiency. As a result, the technology model based on big data brings many benefits to supply chain management in the agri-food industry, such as product quality and transportation planning, accurate information, and time-based decisions, improving product quality and customer satisfaction. Concluding that this system can be applied in an optimal way, seeing that it is a system that generates a lot of costs, but in the future it is possible to see the adequate recovery periods.es_PE
dc.formatapplication/pdfes_PE
dc.format.extentp. 190-196es_PE
dc.language.isoenges_PE
dc.publisherUniversidad Continentales_PE
dc.relationhttps://dl.acm.org/doi/10.1145/3608251.3608257es_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.sourceUniversidad Continentales_PE
dc.sourceRepositorio Institucional - Continentales_PE
dc.subjectAdministración de procesoses_PE
dc.subjectCadena de suministroes_PE
dc.titleTechnological Model Based on Big Data for Good Supply Chain Management in Agribusinesseses_PE
dc.typeinfo:eu-repo/semantics/bachelorThesises_PE
dc.rights.accessRightsAcceso restringidoes_PE
dc.publisher.countryPEes_PE
thesis.degree.nameIngeniero Empresariales_PE
thesis.degree.grantorUniversidad Continental. Facultad de Ingeniería.es_PE
thesis.degree.disciplineIngeniería Empresariales_PE
thesis.degree.programPregrado presencial regulares_PE
dc.identifier.journalICCMS '23: Proceedings of the 2023 15th International Conference on Computer Modeling and Simulationes_PE
dc.identifier.doihttps://doi.org/10.1145/3608251.3608257-
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#5.02.04es_PE
renati.advisor.dni10744358-
renati.advisor.orcidhttps://orcid.org/0000-0003-1865-1293es_PE
renati.author.dni75389210-
renati.author.dni72668144-
renati.author.dni73118877-
renati.author.dni74686647-
renati.author.dni10744358-
renati.discipline413576es_PE
renati.levelhttps://purl.org/pe-repo/renati/level#tituloProfesionales_PE
renati.typehttps://purl.org/pe-repo/renati/type#tesises_PE
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE
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