A Study on Incentive Mechanisms for Agricultural Technological Innovation from an Organizational Perspective

Agricultural science and technology innovation is an important foundation for ensuring food security and promoting sustainable agricultural development. This paper constructs a multi-task principal-agent model between the government and agricultural research institutions to explore how to optimize public R&D incentive mechanisms under conditions of goal conflict and information asymmetry, so as to guide research institutions in allocating effort appropriately between academic-oriented tasks and industry-oriented tasks. The study combines theoretical modeling, case analysis, and numerical simulation: the theoretical model is used to identify the conditions for optimal incentives, the case analysis is used to illustrate how incentive structure imbalances manifest in practice, and the numerical simulation is used to demonstrate the possible effects of incentive correction paths. The theoretical analysis shows that the optimal incentive intensity for a task is positively related to the marginal benefit of its output and negatively related to output uncertainty and the cost coefficient. The effects of the risk aversion coefficient and task substitutability on incentive intensity exhibit threshold conditions, and the direction of these effects depends on the relative levels of the marginal benefits of the two types of tasks. Taking the Jiangsu Academy of Agricultural Sciences as an example, the case analysis finds that academic-oriented tasks receive higher incentives because of their short-term observability, while industry-oriented tasks are under-incentivized due to their long cycles, high risks, and high costs. The numerical simulation further indicates that when the output uncertainty of industry-oriented tasks decreases, the cost coefficient declines, and the marginal benefit increases; the imbalance in incentive allocation may be improved within the scope of the model setting. These conclusions provide policy references for optimizing agricultural research incentive mechanisms and promoting the contribution of agricultural science and technology to sustainable agriculture.