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Mechanism design and equilibrium analysis of smart contract–mediated resource allocation

Jinho Cha et al.

Journal of Industrial and Management Optimization2026https://doi.org/10.3934/jimo.2026037article
AJG 1ABDC B
Weight
0.50

Abstract

Decentralized coordination and digital contracting are becoming essential in complex industrial systems, yet existing approaches often rely on ad-hoc heuristics or purely technical blockchain implementations without a rigorous economic foundation. This study developed a mechanism-design framework for smart contract–mediated resource allocation that jointly embeds efficiency, fairness, and resilience in decentralized coordination. We modeled agent interactions as a contract-clearing game under shared capacity constraints, established the existence and uniqueness of equilibrium, and proposed a decentralized price-adjustment algorithm with provable convergence suitable for real-time operation. Performance was evaluated through extensive synthetic simulations and validated using a representative real-world dataset. In addition to controlled experiments, a long-horizon empirical analysis using financial and macroeconomic data from 2006 to 2025 examined the mechanism under major economic regimes and shock conditions. Results showed that the proposed mechanism consistently reduces inequality and cost while maintaining near-optimal efficiency and rapid recovery following shocks, demonstrating dynamic stability beyond steady state.

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https://doi.org/https://doi.org/10.3934/jimo.2026037

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@article{jinho2026,
  title        = {{Mechanism design and equilibrium analysis of smart contract–mediated resource allocation}},
  author       = {Jinho Cha et al.},
  journal      = {Journal of Industrial and Management Optimization},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.3934/jimo.2026037},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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