Examining the value realization mechanism of agricultural data elements in China: a tripartite evolutionary game analysis

In the era of a burgeoning digital economy, data elements have emerged as pivotal drivers in advancing agricultural digital transformation. This study examines the integration mechanisms of data elements in agriculture through a tripartite evolutionary game model that encompasses government agencies, agricultural technology enterprises, and agricultural operators. Employing stability analysis on strategically selected representative factors, we derive critical insights: (1) The optimal government subsidy coefficient should remain below 0.5, as excessive subsidies (β ≥ 0.5) impose unsustainable fiscal burdens while failing to effectively stimulate agricultural data utilization. (2) Agricultural operators’ digital literacy exhibits a positive correlation with their willingness to participate. When operator literacy is high (α > 0.5), they are more likely to participate in agricultural data utilization. (3) Strategic interactions reveal that governments tend to initiate guidance when operator literacy is low (θ < 0.5), whereas technology enterprises adopt passive strategies under similar conditions. (4) A critical threshold of 5 for project entrustment fees governs tripartite decision-making: exceeding this value triggers government disengagement, subsequently leading to corporate passivity and operator non-participation. (5) Low digital literacy weakens the effectiveness of high-subsidy policies, respectively, leading agricultural technology enterprises and agricultural operating entities to tend towards passively leading and not participating in agricultural data utilization.