COHERENCE OF ECONOMIC DECISIONS IN AN ENVIRONMENT OF INFORMATION TURBULENCE: THE IMPACT OF INSTITUTIONAL COMMUNICATION

This study develops a computational model to analyse how information structures and behavioural heterogeneity affect trust dynamics and the coherence of economic behaviour within a society. The research integrates Bayesian learning mechanisms with agent-based modelling to simulate how individuals characterised by varying cognitive styles - optimists, conservatives, cynics, novices - update their trust in institutional versus disinformative sources over time. The model investigates how different societal configurations, under varying dominance of fake or institutional information channels, influence aggregate behavioural coherence and the system’s adaptive capacity. The analysis also considers the role of institutional feedback mechanisms in amplifying or mitigating the effects of disinformation shocks. Methodologically, the model simulates multiple societal scenarios, combining dynamic belief adjustment, probabilistic information signals, and multi-source weighting. Coherence is measured as the entropy-based convergence of agent decisions, while trust evolves as an endogenous variable reacting to perceived signal reliability. The simulations account for multiple time steps, asymmetric source quality, and cognitive diversity within agent populations. The results show that behavioural coherence in economic actions is highly sensitive to the prevailing type of information and the dominant cognitive profiles in society. Adaptive societies with a majority of fast-learning agents restore coherence more quickly when institutional sources dominate. Conversely, pessimistic or highly inert societies struggle to recover under conditions of misinformation. Establishing stable institutional channels can gradually restore aggregate trust and behavioural alignment, even in disinformation-dominant environments. The study's novelty lies in combining cognitive agent typologies, endogenous trust dynamics, and coherence metrics within a unified simulation framework. The findings have practical implications for designing strategic communications, institutional policy-making, and resilience planning in the face of informational crises.