Emergency lateral-transshipment cooperation and artificial-intelligence in Tunisia: A case study of the "Tunisian Date and Date Product Society (DTA)"

• Dr. Ahmed Ben Youssef

  Author

Integrating artificial intelligence into its inventory and supply chain management processes allows the Tunisian Date Palm (DTA) to better anticipate its logistics and production needs. For example, AI is used to forecast periods of high demand and adjust production based on global market trends. This AI system not only minimizes storage costs but also reduces resource waste by optimizing delivery and storage time management. AI technologies also help automate date traceability from harvest to shipment, ensuring quality and transparency for international customers.
Furthermore, the DTA has integrated AI-powered data analytics tools to improve the efficiency of its distribution network by identifying potential bottlenecks and optimizing transport routes. This collaboration with Tunisian and international technology companies has enabled the integration of intelligent supply chain management and shipment tracking systems. Lateral transshipment has reduced the transit time of dates while guaranteeing their freshness, a crucial aspect for DTA's reputation, which is committed to offering superior quality dates.

1. Dr. Ahmed Ben Youssef

   Faculty of Economic Sciences and Management, University of Tunis El Manar, Tunis, Tunisia

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