Mechanism Design for Incentive-Compatible Capacity Exchange in Intelligent Manufacturing Platforms
Keywords:
mechanism design, incentive compatibility, capacity exchange, intelligent manufacturing, platform governance, industrial internet of things, fairness, sustainability, digital twins, multi-agent systemsAbstract
The rise of intelligent manufacturing platforms has enabled distributed production resources to be shared and coordinated across organizational boundaries, creating new opportunities for flexible capacity utilization. However, the formation of efficient and stable capacity exchanges relies on the voluntary participation of self-interested firms that hold private information about their production capabilities, costs, and strategic valuations. Designing mechanisms that elicit truthful reporting and ensure incentive compatibility while achieving system-wide objectives constitutes a core challenge at the intersection of operations, artificial intelligence, and economic systems. This paper presents a comprehensive systems-level analysis of mechanism design for capacity exchange platforms, focusing on the architectural, governance, infrastructure, and policy dimensions that underpin incentive-compatible resource allocation. The discussion explores the structural trade-offs between centralized optimization and decentralized negotiation, the role of trust and reputation in mitigating strategic misrepresentation, and the integration of real-time sensing and digital twin technologies in enabling verifiable capacity claims. The paper further examines fairness considerations in multi-stakeholder environments, the long-term sustainability of exchange mechanisms under dynamic market conditions, and the regulatory implications of algorithmically mediated capacity markets. By synthesizing perspectives from mechanism design theory, distributed systems, and socio-technical infrastructure studies, the analysis provides a forward-looking view on designing robust and equitable capacity exchange frameworks that can support the next generation of intelligent manufacturing ecosystems.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
