Empirical analysis identifies challenges in cost management of supply chain collaboration, suggesting solutions through AI and blockchain.
This study investigates cost management mechanisms for supply chain collaboration in logistics enterprises amid digital transformation. Empirical analysis of leading firms reveals three core challenges: 1. Information silos exacerbate the bullwhip effect, causing >30% demand forecasting deviations and 22% resource mismatch rates; 2. Technical bottlenecks constrain collaborative efficiency, with cross-system interoperability below 40% and AI sorting error rates reaching 4.7%; 3. 73% of enterprises face data fragmentation due to absent benefit distribution mechanisms. A tri-dimensional optimization framework is proposed: Technology empowerment: AIoT-integrated systems reduce empty-load rates by 18 percentage points, while smart warehouses cut costs by 15.8%; Managerial innovation: Cross-enterprise collaboration committees accelerate inventory turnover by 28%; Policy adaptation: Multimodal transport platforms reduce per-container logistics costs by ¥1,000. Blockchain trust mechanisms shorten quality dispute resolution cycles by 60%, while resource sharing lowers trunk-line costs by 25%. Implementation demonstrates synergistic pathways to reduce China's social logistics costs from 14.1% toward the national target of 13.5% of GDP.
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Q Chen (2025) studied this question.
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