Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12394/16957
Title: | Technological Model Based on Big Data for Good Supply Chain Management in Agribusinesses |
Authors: | Campos Contreras, Marco Antonio Cajachagua Guerreros, Diego Castañeda Vargas, Pedro Segundo Pantoja Vega, Jean Carlos Palomino Jaime, Cristian Andres |
metadata.dc.contributor.advisor: | Castañeda Vargas, Pedro Segundo |
Keywords: | Administración de procesos Cadena de suministro |
Publisher: | Universidad Continental |
Issue Date: | 2024 |
metadata.dc.date.available: | 27-Mar-2025 |
Citation: | Campos, M., Cajachagua, D., Castañeda, P., Pantoja, J. y Palomino, C. (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. |
metadata.dc.identifier.doi: | https://doi.org/10.1145/3608251.3608257 |
Abstract: | Agribusiness 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. |
metadata.dc.relation: | https://dl.acm.org/doi/10.1145/3608251.3608257 |
Extension: | p. 190 - 196 |
metadata.dc.rights.accessRights: | Acceso restringido |
metadata.dc.source: | Universidad Continental Repositorio Institucional - Continental |
Appears in Collections: | Tesis |
Files in This Item:
File | Description | Size | Format | |
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Informe_Turnitin.pdf Restricted Access | Informe de Turnitin | 1.48 MB | Adobe PDF | View/Open Request a copy |
IV_FIN_114_Autorización_2024.pdf Restricted Access | Autorización | 307.59 kB | Adobe PDF | View/Open Request a copy |
IV_FIN_108_TE_Campos_Cajachagua_Castañeda_Pantoja_Palomino_2024.pdf | Resumen | 987.91 kB | Adobe PDF | View/Open |
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