Artificial intelligence-based strategies for supply chain inventory management

 

Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Awduron: Johan Sebastian, Riascos-Guerrero, Jhoan Andres, Galván-Colonia, Esteban, Pincay-Lozada, Jorge Luis
Fformat: artículo original
Statws:Versión publicada
Dyddiad Cyhoeddi:2024
Disgrifiad:Inventory management stands as an essential component in the supply chain of any company, playing a crucial role in reducing costs and ensuring customer satisfaction. In the current business environment, characterized by its rapid evolution and high competitiveness, artificial intelligence or AI emerges as an innovative tool capable of transforming the way companies approach this management. The application of advanced machine learning algorithms makes it possible to process large volumes of historical sales data, purchasing patterns, market trends and economic conditions, contributing significantly through the accurate prediction of future demand. This analytical capability enables companies to anticipate market needs and adjust their inventory levels effectively, avoiding shortages or overstock situations. In addition to optimizing the supply chain, artificial intelligence identifies bottlenecks and suggests improvements in logistics and distribution, improving operational efficiency and ultimately increasing customer satisfaction. In this scenario, the strategic application of artificial intelligence consolidates the competitive position of companies by proactively adapting their inventory management practices to the demands of today’s market.
Gwlad:Portal de Revistas TEC
Sefydliad:Instituto Tecnológico de Costa Rica
Repositorio:Portal de Revistas TEC
Iaith:Español
OAI Identifier:oai:ojs.pkp.sfu.ca:article/7271
Mynediad Ar-lein:https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/7271
Allweddair:Artificial intelligence
supply chain management
business productivity
demand forecasting
operational efficiency
Inteligencia artificial
gestión de la cadena de suministro
productividad empresarial
predicción de la demanda
eficiencia operativa