In social systems that are hierarchically constructed from various decision-makers, consensus building is becoming more difficult due to the complex relationships among various systems, and decision support by information technology is required. In social simulation, which is the technology we are focusing on, models that can reflect the intentions of various stakeholders are required based on the concept of multi-stakeholder processes. However, conventional modeling methods are applied independently at each level, making it difficult to achieve both a macro evaluation of the entire system and a micro evaluation of the detailed parts. Therefore, this paper proposes a multi-scale modeling method that can model each system component at the spatio-temporal level. Specifically, we propose a method to organize decision-makers in a social system, construct a decision model on an appropriate spatio-temporal scale, and then integrate them based on two types of relationships among decision-makers: codes of conduct as their constraint relationship and social consciousness shared by the entire society. As a case study, we apply the proposed method to the COVID-19 policy, and verify through computer experiments that the proposed model structure is capable of representing stakeholder decision-making regarding COVID-19.
