Big Data e Inteligencia Artificial para la toma de decisiones: un enfoque en la cadena de suministro sostenibles
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Este estudio analiza la importancia del Big Data y la Inteligencia Artificial (IA) en la toma de decisiones dentro de cadenas de suministro sostenibles; para ello, se llevó a cabo una revisión sistemática de literatura siguiendo la metodología PRISMA. Se utilizó la herramienta VOSviewer para clasificar y representar gráficamente los datos relacionados con citación de autores, análisis de palabras clave, tendencias a través de los años y países que más han publicado sobre el tema. La investigación se basó en artículos académicos revisados por pares, publicados entre 2018 y 2025, y disponibles en la base de datos Scopus y Google Académico. Los resultados obtenidos revelan que la combinación de Big Data e IA no solo optimiza la eficiencia logística, sino que también impulsa avances significativos en sostenibilidad ambiental, social y económica. Técnicas como el análisis predictivo, el aprendizaje automático (machine learning) y el Internet de las Cosas (IoT) facilitan la automatización de procesos, el monitoreo en tiempo real de productos y la reducción de la huella ecológica. Un hallazgo clave es el modelo "Artificial Intelligence of Everything" (AIoE), propuesto por Nozari (2024), que emerge como un enfoque innovador para digitalizar las cadenas de suministro sin comprometer su sostenibilidad.
Como conclusiones principales, se destaca la importancia de estas tecnologías para desarrollar cadenas de suministro resilientes, transparentes y ecológicas, como futuras áreas de investigación; se recomienda explorar la implementación práctica del AIoE, la sinergia con blockchain, el refinamiento de modelos predictivos y la capacitación en habilidades digitales alineadas con la sustentabilidad.
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