Knowledge Graph-Driven Trust Evaluation for Cross-Enterprise Capacity Collaboration
Keywords:
knowledge graph, trust evaluation, cross-enterprise collaboration, capacity sharing, semantic interoperability, industrial symbiosis, decentralized governanceAbstract
Cross-enterprise capacity collaboration has emerged as a strategic imperative in contemporary manufacturing and service ecosystems, enabling firms to share underutilized resources, respond to demand volatility, and reduce capital expenditure. However, the formation and sustenance of such collaborative networks hinge critically on trust among autonomous, often competing, entities. Traditional trust evaluation mechanisms, rooted in ratings, contractual clauses, or centralized intermediaries, fail to capture the rich relational, contextual, and historical interdependencies that characterize multi-party industrial partnerships. This paper presents a knowledge graph-driven framework for trust evaluation that encodes enterprises, capacities, transactions, and their complex interrelations into a machine-readable semantic fabric. Drawing from ontological engineering, distributed systems, and socio-cognitive trust theories, the proposed architecture leverages graph-based reasoning to infer trustworthiness from heterogeneous evidence streams, including past performance, capability alignment, regulatory compliance, and network position. The discussion addresses system-level design trade-offs between expressiveness and computational scalability, governance models for decentralized knowledge curation, and the integration of verifiable credentials to anchor trust in off-chain realities. Furthermore, the paper examines robustness against adversarial manipulation, fairness in trust scoring across asymmetrically resourced participants, and the sustainability implications of long-term collaboration ecosystems. By synthesizing cross-domain insights from digital twins, industrial symbiosis, and federated machine learning, this work articulates a socio-technical infrastructure where trust is not merely a score but a continuously negotiated and context-aware property, enabling resilient and equitable capacity markets. The analysis concludes with policy considerations for public-private governance of shared industrial knowledge graphs, emphasizing interoperability, data sovereignty, and algorithmic transparency as foundational requirements for the next generation of circular and networked production systems.
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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.
