Technological Model Based on Big Data for Good Supply Chain Management in Agribusinesses

Marco Antonio Campos Contreras, Cristian AndréS Palomino Jaime, Jean Carlos Pantoja Vega, Pedro Segundo Castañeda Vargas, Diego Ricardo Cajachagua Guerreros

Producción científica: Libro o Capítulo del libro Contribución a la conferenciarevisión exhaustiva


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.

Idioma originalInglés estadounidense
Título de la publicación alojadaProceedings of ICCMS 2023 - 15th International Conference on Computer Modeling and Simulation
EditorialAssociation for Computing Machinery
ISBN (versión digital)9798400707919
EstadoIndizado - 16 jun. 2023
Evento15th International Conference on Computer Modeling and Simulation, ICCMS 2023 - Dalian, China
Duración: 16 jun. 202318 jun. 2023

Serie de la publicación

NombreACM International Conference Proceeding Series


Conferencia15th International Conference on Computer Modeling and Simulation, ICCMS 2023

Nota bibliográfica

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© 2023 ACM.


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