Artificial intelligence-based strategies for supply chain inventory management
保存先:
| 著者: | , , , |
|---|---|
| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2024 |
| その他の書誌記述: | 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. |
| 国: | Portal de Revistas TEC |
| 機関: | Instituto Tecnológico de Costa Rica |
| Repositorio: | Portal de Revistas TEC |
| 言語: | Español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/7271 |
| オンライン･アクセス: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/7271 |
| キーワード: | 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 |