AI-Blockchain synergy for resilient agricultural supply chains: an evolutionary game analysis

Abstract

Agricultural supply chain finance faces enduring challenges stemming from information asymmetry, seasonal fluctuations, and credit constraints. This study develops an integrated framework combining artificial intelligence and blockchain technologies to strengthen supply chain resilience. We establish a tripartite evolutionary game model engaging banks, core enterprises, and small and medium-sized enterprises, incorporating dynamic technical parameters alongside critical operational variables including inventory dynamics, seasonal financing patterns, and heterogeneous agent behaviours. Through evolutionary game theory and systematic numerical simulations, we examine how AI-blockchain synergy influences strategic evolution and stability conditions. The study introduces a quantifiable resilience index R and identifies dual threshold conditions governing effective technological collaboration. Based on these findings, we design coordinated financing and inventory management strategies. Our results demonstrate that the proposed mechanism reduces agency costs, enhances credit assessment and demand forecasting accuracy, and directs the system toward Pareto-optimal equilibrium. This creates a self-reinforcing cycle where technological advancement drives operational improvements that subsequently strengthen systemic resilience. These findings provide theoretical foundations, analytical tools, and practical guidance for developing data-enriched, resilient agricultural supply chains.

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ORCID for Xiaoyan Xu: orcid.org/0000-0003-4565-5986

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