Feedback Topology and Adaptive Governance in Business Development Systems

Abstract

Research on business development systems provides limited explanation of how governance structures adapt to structural misalignment under turbulent conditions. Conventional regulatory approaches rely on fixed control parameters that constrain adaptive response under nonstationary conditions. This study develops a computational state space modelling framework for adaptive regulatory architecture within a business development system. The framework specifies governance intensity, coordination coherence and strategic misalignment as coupled state variables and connects them through recursive feedback dynamics. Monte Carlo simulations evaluate alternative regulatory topologies under repeated disturbance conditions. Results indicate that proportional endogenous scaling shortens recovery intervals, strengthens corrective feedback alignment and reduces long‐run structural variance relative to fixed‐gain and exogenous adjustment structures. Regulatory topology thus shapes resilience performance in dynamic business development systems. Findings contribute a computational explanation of adaptive governance and provide design principles for scalable governance intensity under environmental turbulence.