In China, agricultural logistics systems are still confronted with persistent challenges, including excessive circulation links, high post-harvest losses, and elevated transaction costs. As a result, market mismatches characterized by unsold produce and difficulties in procurement are frequently observed. Increasing attention has therefore been drawn from policymakers, industry practitioners, and academic researchers. Existing studies are primarily focused on infrastructure investment, information system development, and the optimization of individual logistics models. However, systematic investigations into multi-agent collaborative governance and stable incentive mechanisms under digital-intelligence platforms remain scarce. To address this gap, a conceptual framework for an alliance-based hybrid agricultural logistics model was constructed by synthesizing China’s logistics practices with international experience. Within a multi-principal–multi-agent theoretical framework, a supply chain consisting of agricultural suppliers, digital platform enterprises, and third-party logistics providers was examined. An equity incentive mechanism was introduced to analyze participants’ effort levels, payoff structures, and cooperation stability. Simulation results demonstrate that the lead agent’s additional returns increase significantly as the equity share rises, accompanied by enhanced effort provision. The lead principal’s logistics expenditures decrease with higher equity allocation, while the payoffs of subordinate principals and agents remain largely stable. A Pareto-improving outcome is thus generated for all supply chain participants. The findings offer a novel theoretical explanation for the recurring problem of unsold agricultural products and provide valuable managerial insights for the design of logistics structures and incentive mechanisms in digital-intelligence platform environments.
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