Artificial Intelligence in Collaborative Data Sharing for Intra-Company Logistics
insight, adaptive processes characterized by heightened resilience and scalability, and circular data economies enabled by the sustainable extension and reutilization of trusted, high-fidelity data assets across the collaborative ecosystem.
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THREE WAYS AI SCALES VALUE IN COLLABORATIVE LOGISTICS DATA SHARING
The ICL Testbed provides a unique empirical window into how collaborative, multi-partner datasharing architectures enable AI-driven value creation. Analysis of this living laboratory reveals that AI creates value in such collaborative logistics data-sharing environments across three interconnected dimensions( see Figure 2-1). Figure 2-1 visualizes the three interconnected AI layers: data-oriented Digital Twin( light blue), information-oriented Services( blue) [ 1 ] as well as business value-oriented( dark blue).
The first dimension encompasses intelligent data provisioning and sensor data preparation that enables deep operational integration across partner systems. The second centers on AI-based analytics that enables decision support and facilitate continuous process optimization. The third dimension involves the horizontal expansion of these AI capabilities toward adjacent assets, supplementary data sources, and entirely new business scenarios within the broader logistics ecosystem. We refer to this scaling dynamic as the“ One Step Further” logic. This mechanism, which transforms successful core implementations into platforms for combinatorial and unanticipated innovation, will be explored in depth in Section 5.
Business Value |
Track & Trace |
… |
Sec. 5
Extension to Adjacent Scenarios
|
Services |
Logistics Dashboard |
… |
AI |
AI-Supported Analytics and Optimization |
Sec. 4 |
Digital Twins
Assets
Collaborative Data Sharing AI
…
AI …
Operational Integration through Intelligent Data Provisioning
Sec. 3
Figure 2-1: Three Ways of AI Value Contribution in the ICL Testbed
EDM Association – Journal of Innovation 129