Big data y cadenas de suministros un binomio complejo para américa latina

Raúl Rodríguez-Luna; Margareth Mercado-Pérez; Mariana Escobar-Borja

doi:10.15649/2346030X.825

Autores/as

Raúl Rodríguez-Luna Universidad Cooperativa de Colombia https://orcid.org/0000-0002-8718-2681
Margareth Mercado-Pérez Universidad Cooperativa de Colombia
Mariana Escobar-Borja Universidad Cooperativa de Colombia

DOI:

https://doi.org/10.15649/2346030X.825

Palabras clave:

big data, redes neuronales, cadenas de suministro, modelos logit

Resumen

Este documento evalúa algunas medidas de rendimiento que afectan el uso de Big Data (BD) en la Cadena Oleaginosas, Aceite y Grasas en América Latina (CSM) el trabajo tiene el respaldo teórico de Big Data (BD), redes neuronales (RN) y cadenas de suministro (CSM), el articulo responde cuatro interrogantes ¿en qué actividades y operaciones productivas se está aplicando Big Data? ¿Determinar algunas variables de desempeño de las cadenas de suministro que afectan variabilidad del Big Data a partir de la teoría de las CSM? ¿Qué beneficios agregan las redes neuronales a las cadenas de suministro?, estimar la variabilidad de los procesos de BD por efectos de (CSM), para estos se utiliza la regresión logística, los datos provienen de distintos eslabones de CSM, los hallazgos sugieren que para la muestra estudiada las principales medidas de variabilidad para el BD en las CSM son, el tipo de formación del personal, la subcontratación en BD, aumento en las ventas, los tipos de pagos de pago por el servicio e-comerce y el uso de modelos predictivos incorporados en la cadena para prevenir fallas y proyectarlas.

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