He is working on elucidating the causal mechanisms of various social and economic phenomena, the lack of understanding of which he believes to be the root cause of many societal problems. His approach involves using novel methodology he has developed: mechanism-oriented agent-based modeling. He has created an agent-based model of fundamental economic systems using C++ and object-oriented programming. In this model, GDP is calculated using double-entry bookkeeping, mirroring real-world practices. He plans to expand this model to encompass a broader range of economic phenomena, including the monetary system (involving stocks and debts), international trade, foreign exchange rates, corporate growth, and the emergence of new businesses. A key technical challenge of this methodology is the requirement for users to possess sufficient programming skills. This is because it involves translating experimentally assumed model structures into programming code, during the iterating process of finding the indispensable factors to reproduce the key characteristics of the phenomenon. Therefore, developing user-friendly software that can be used by researchers without extensive programming expertise is also a crucial aspect of his research.

Emeritus Professor Shigeaki Ogibayashi graduated from the Department of Physics at Tohoku University in 1969 and earned his master's degree in physics in 1971. He subsequently joined Nippon Steel Corporation as a research engineer, where he conducted research in metallurgy and steel solidification, making significant contributions to the R&D of numerous technologies within the steel industry. In 1992, he received his Ph.D. from the School of Metallurgy at the University of Tokyo. Following his retirement from Nippon Steel in 1997, he joined the Chiba Institute of Technology as a professor in the Department of Management Information Science. He played a key role in establishing a new faculty of social systems science and a new graduate school program. During this time, he also actively engaged in research on agent-based modeling and simulation. Notably, he developed an agent-based model of an economic system capable of calculating GDP using double-entry bookkeeping, mirroring real-world practices. In 2014, he formulated a new principle for agent-based modeling, which he termed "mechanism-oriented agent-based modeling." This principle enables the elucidation of the causal mechanisms of social phenomena through a series of systematic computer experiments. Since then, he has dedicated himself to validating this principle by applying it to various socio-economic phenomena. Although he retired from the Chiba Institute of Technology in March 2017, Professor Ogibayashi continues to actively research and apply this new approach, mechanism-oriented agent-based modeling, to fundamental economic phenomena in the goods market and various social issues, including bullying and pandemics. The infectious disease model presented today exemplifies his ongoing research in this area. Reference: "Agent-Based Modeling as a Scientific Methodology for Understanding Causal Mechanisms in Social Phenomena: A Pandemic Model Incorporating Immune Cells and Antibodies". This implies that the root cause of each phenomenon lies within the specific system structure – the set of rules and variables that govern the behavior of each type of decision-maker. Agent-based modeling, an entirely bottom-up approach, enables us to construct artificial societies that mirror this principle. In these models, the cause of a macro-level phenomenon is expressed in terms of the model's structure: the set of factors essential for reproducing the phenomenon's key characteristics. Through systematic computer experiments, we can identify these crucial factors and, consequently, uncover the underlying causal mechanisms of the phenomenon's emergence. I term this approach "mechanism-oriented agent-based modeling" and propose it as a valuable scientific methodology for investigating the causes of various social phenomena. This methodology's applicability extends beyond social systems. In biological systems, such as the human body, disease and recovery are driven by the roles and interactions of individual components. This presentation outlines the principles and procedures of mechanism-oriented agent-based modeling. To illustrate its application, I present a pandemic model that simulates infection and recovery processes at the individual level, incorporating heterogeneity in immunity and antibody levels. My analysis revealed that the most critical factor in pandemic convergence is the immune-boosting effect of fever.