Forecasting accuracy influence on logistics clusters activities: The case of the food industry

摘要: Abstract The current approaches to supply chain management generate large amounts of food waste due the growing urbanization levels, increasing consumer demand for organic products and growth e-commerce distribution channel. These trends require organizations rethink their management, so that they could cope with upcoming challenges. This research paper focuses on ways a logistics cluster can provide abilities share information thus improve forecasting accuracy. main novelty has been work out collaborative technological strategy which promotes sharing in order accuracy inventory control better alignment supply. secondary contribution article is determination influence different market sizes, types consideration integration. Lastly, sensitivity analysis completed identify optimal size provides support when implementing proposed practice. For results validation we have implemented an agent-based model chain. Our confirmed increases multiple scenarios. Moreover, integration beneficial perfect competition market; however, its positive effect less significant oligopoly market. findings should be taken into developing business forming clusters. usage machine learning algorithms process adaptation capabilities members. emerges as system resilience it improves supply, reduces levels maintains higher nutrition value. ensure long-term sustainable development