During the "14th Five-Year Plan" period, Guizhou has achieved a historic low by reducing the proportion of total social logistics costs to GDP to 14.3% through infrastructure improvements and digital technology empowerment; however, there remains room for optimization compared to developed regions. To this end, Zhang Hui, a member of the Guizhou Provincial Committee of the Chinese People's Political Consultative Conference (CPPCC) and Chairman of Full Truck Alliance, suggested during the 2026 Two Sessions of Guizhou Province that Guizhou could explore creating a "Digital Logistics Brain" to further reduce social logistics costs by breaking down data collaboration barriers. As Guizhou enters a new phase of development towards the "15th Five-Year Plan," it has clearly stated its direction to equally prioritize hardware upgrades and qualitative improvements, enhance the public-railway-water-aviation logistics network, and strengthen the development of multimodal transport and digital-intelligent construction. Zhang Hui stated that by leveraging Full Truck Alliance's core advantages in digital freight and logistics ecosystem construction, accelerating government-enterprise coordination and promoting industrial integration can not only further reduce Guizhou's social logistics costs but also help build an integrated "channel + logistics + industry" pattern for transport, production, and trade. Zhang Hui suggested exploring the establishment of a "Digital Logistics Brain"—a unified provincial logistics data sharing platform for Guizhou—led by departments such as the Development and Reform Commission and Transport, and jointly built with leading logistics enterprises within the province. By integrating data from provincial logistics infrastructure such as highways, railways, aviation, and ports, along with government data from industry and commerce, taxation, and customs, the platform would achieve "one-time declaration, data sharing, and multi-department linkage." Zhang Hui believes that using big data analytics to optimize logistics route planning, capacity scheduling, and warehouse layout can specifically address the "information silos" issue in multimodal transport, thereby constructing a modern logistics development model characterized by "data-driven operations, government-enterprise collaboration, and a thriving ecosystem." This would fully unleash Guizhou's advantage as a key node in the New Western Land-Sea Corridor. "For instance," Zhang Hui said, "deeply integrating channel resources like the Qian-Guang Railway Express and China-Europe Railway Express with the digital platform can further enhance the efficiency of rail-sea and road-rail intermodal transport, reducing transfer costs." Furthermore, to address the bulk transport demands for Guizhou's characteristic agricultural products and industrial goods, relevant parties could jointly develop "digital intermodal transport + customized service" solutions, achieving "door-to-door" full-process visual tracking. Promoting efficient models like "Railway Express Clearance" and "Export Direct Clearance," and expanding the coverage of "Combined Ports," would enable Guizhou's goods to quickly connect via digital matching to 37 Southeast Asia sea routes nationwide, reducing empty truck rates and transfer time. Zhang Hui also recommended continuing and expanding the differentiated toll policy for expressways, offering additional discounts for new energy trucks dispatched through the digital platform, thereby promoting cost reduction and efficiency gains in green transport. Against the backdrop of rapid digital economic development, the logistics industry has an even greater need for smart logistics talent with composite skills. To this end, Zhang Hui suggested that Guizhou could explore establishing a "Digital Logistics Industry College," offering specialized programs in intelligent dispatch and logistics big data analysis, and cultivating practical talent through a "school-enterprise cooperation, work-integrated learning" model. Establishing a special fund for digital logistics innovation to support joint research by Full Truck Alliance, Guizhou universities, and research institutions on cutting-edge technologies like autonomous heavy trucks and logistics AI large models would promote the local application and transformation of scientific research achievements in Guizhou.
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