Research on Structural Models of Decision-Making, Growth, and Control Adopted by International Conference ISSS 2026
Independent research project Cycle Structure Lab announced that its research on structural models of decision-making, growth, and control has been adopted by the International Society for the Systems Sciences (ISSS) 2026. This study focuses on the interaction of forces that generate change, amplify reinforcement, and select/control them under constraints, contributing to governance design for AI implementation and the stabilization of complex systems.
📋 Article Processing Timeline
- 📰 Published: May 2, 2026 at 21:00
- 🔍 Collected: May 2, 2026 at 12:31
- 🤖 AI Analyzed: May 2, 2026 at 12:32 (1 min after Collected)
Independent research project Cycle Structure Lab is pleased to announce that its research on structural models of decision-making, growth, and control has been adopted by the International Society for the Systems Sciences (ISSS) 2026.
The adopted research focuses on the interaction of forces that generate change, amplify reinforcement, and select/control them under constraints, presenting a structural model for sustainable decision-making even under constraints. It proposes a perspective that the destabilization of complex systems can arise not merely from a lack of progress, but also from reinforcement progressing while the updating of constraints fails to keep pace.
In this research, even when superficial expansion continues, if the updating of selection and redistribution is delayed, the state where apparent growth and governability diverge is termed "structural drift." For example, while usage expansion and sales metrics may look favorable, if cancellation rates, operational load, and exception handling costs gradually increase, fragility may accumulate beneath the surface, even with good surface growth indicators.
In recent years, with the advancement of AI and automation, there has been an increase in cases where the unit for starting PoCs becomes ambiguous due to premature conceptualization, or operational load swells due to unclear demarcation of responsibilities between departments. Cycle Structure Lab addresses these issues not as individual operational problems, but as structural problems where multiple factors interact. It promotes research and practical support that organizes the relationships among decision-making, control, and updating.
Academically, this research is positioned within the contexts of systems science, cybernetics, organizational theory, and complex systems. Practically, it also connects to the following issues:
* Governance design for AI introduction and utilization
* PoC design, evaluation metric design, and organization of implementation order
* Clarification of responsibility demarcation involving multiple departments and entities
* Control, prioritization, and resource redistribution during growth phases
* Diagnosis of rigidification, over-optimization, and drift occurring after operational expansion
The International Society for the Systems Sciences (ISSS) is an international academic society that deals with systems science, complex systems, organizations, and social systems, providing an interdisciplinary venue for both researchers and practitioners. Cycle Structure Lab will continue to advance structural research spanning areas such as decision-making, AI governance, institutional design, and operational control, exploring the potential for connecting theory and practice.
Adopted Research
Reinforcement under Constraint: A Systems Model of Forward, Cycle, and Backward Dynamics (FxCxB)
International Society for the Systems Sciences (ISSS) 2026
About Cycle Structure Lab
Cycle Structure Lab is an independent research project that studies the structure of growth, allocation, and control under constraints. It conducts structural research connecting theory and practice on themes such as AI implementation, operational control, organizational decision-making design, and sustainable growth.
Contact Information for this matter
Yoshiaki Hori
Cycle Structure Lab
Email: cycle.structure.lab@gmail.com
The adopted research focuses on the interaction of forces that generate change, amplify reinforcement, and select/control them under constraints, presenting a structural model for sustainable decision-making even under constraints. It proposes a perspective that the destabilization of complex systems can arise not merely from a lack of progress, but also from reinforcement progressing while the updating of constraints fails to keep pace.
In this research, even when superficial expansion continues, if the updating of selection and redistribution is delayed, the state where apparent growth and governability diverge is termed "structural drift." For example, while usage expansion and sales metrics may look favorable, if cancellation rates, operational load, and exception handling costs gradually increase, fragility may accumulate beneath the surface, even with good surface growth indicators.
In recent years, with the advancement of AI and automation, there has been an increase in cases where the unit for starting PoCs becomes ambiguous due to premature conceptualization, or operational load swells due to unclear demarcation of responsibilities between departments. Cycle Structure Lab addresses these issues not as individual operational problems, but as structural problems where multiple factors interact. It promotes research and practical support that organizes the relationships among decision-making, control, and updating.
Academically, this research is positioned within the contexts of systems science, cybernetics, organizational theory, and complex systems. Practically, it also connects to the following issues:
* Governance design for AI introduction and utilization
* PoC design, evaluation metric design, and organization of implementation order
* Clarification of responsibility demarcation involving multiple departments and entities
* Control, prioritization, and resource redistribution during growth phases
* Diagnosis of rigidification, over-optimization, and drift occurring after operational expansion
The International Society for the Systems Sciences (ISSS) is an international academic society that deals with systems science, complex systems, organizations, and social systems, providing an interdisciplinary venue for both researchers and practitioners. Cycle Structure Lab will continue to advance structural research spanning areas such as decision-making, AI governance, institutional design, and operational control, exploring the potential for connecting theory and practice.
Adopted Research
Reinforcement under Constraint: A Systems Model of Forward, Cycle, and Backward Dynamics (FxCxB)
International Society for the Systems Sciences (ISSS) 2026
About Cycle Structure Lab
Cycle Structure Lab is an independent research project that studies the structure of growth, allocation, and control under constraints. It conducts structural research connecting theory and practice on themes such as AI implementation, operational control, organizational decision-making design, and sustainable growth.
Contact Information for this matter
Yoshiaki Hori
Cycle Structure Lab
Email: cycle.structure.lab@gmail.com