为了解决BOT项目实践中超额收入分配不合理、收入不足时的补贴额确定缺乏科学依据的关键问题，本课题拟构建BOT项目超额收入分配及补贴决策模型并加以应用验证。（1）识别BOT项目超额收入分配与补贴的影响因素，建立因果关系图；（2）以项目公司的超额收入分配比例最大化作为项目公司的决策目标函数，以社会福利最大化作为约束条件，建立超额收入分配决策模型，设计超额收入分配比例随超额收入值变化的决策方法；（3）针对非项目公司原因和项目公司原因两种情况，应用改进的二项式期权模型求得最低收入保证期限和额度，建立政府、项目公司、社会公众三方满意的BOT项目补贴决策模型；（4）针对纯经营性和准经营性两类BOT项目，对超额收入分配和补贴决策模型进行案例应用验证和适用性分析。 本课题研究是对BOT项目决策理论与方法的补充与完善，研究成果可以为政府与项目公司合理确定超额收入分配比例与补贴、分担风险提供决策支持。

In order to solve the key issues that the allocation of excess revenue is unreasonable and the subsidy for revenue shortfall is lack of scientific basis in the practice of BOT projects, it is proposed to construct the decision-making models on allocation of excess revenue and subsidy for BOT projects, and then illustrate the proposed models. (1) Identify the influencing factors of excess revenue allocation and subsidy, as well, build the causal loop diagrams for BOT projects; (2) On condition that maximizing the portion of excess revenue allocation is regarded as the decision-making objective function for private sector, and maximizing social welfare is regarded as the constraint condition, construct a decision-making model on allocation of excess revenue, and design a method that makes the portion vary with the excess revenue value; (3) According to the faults of the private sector and others, apply the improved binomial lattice model to obtain the guarantee period and value of minimum revenue guarantee, and construct a decision-making model on subsidy for BOT projects which satisfies the requirements of the government, the private sector and the general public; (4) In view of the pure-commercial BOT projects and quasi-commercial BOT projects, case studies are applied to illustrate and analyze the decision-making models on allocation of excess revenue and subsidy. The research is expected to complement and improve the decision-making theories and methods for BOT projects, and the research findings can provide supports of making decisions on allocation of excess revenue, subsidy and risk sharing for both the government and private sector.