Modeling decentralized markets under complexity: A behavioral and computational approach

Decentralized markets characterized by heterogeneous agents, bounded rationality, and interaction-driven dynamics pose significant challenges to conventional analytical approaches. Models based on representative agents, equilibrium assumptions, and historical data often fail to capture adaptation, feedback mechanisms, and the endogenous emergence of market organization. This paper addresses this methodological gap by proposing a framework for analyzing such markets using agent-based modeling. The study adopts a theoretical and methodological approach grounded in complexity economics and computational modeling. It systematizes the core elements required to model decentralized markets, including agent heterogeneity, behavioral rules, local interactions, and dynamic processes, and organizes them into a structured framework for model construction, simulation, and validation. The results show that agent-based modeling provides a more suitable analytical architecture for representing economic systems in which coordination emerges from decentralized interactions. By explicitly incorporating behavioral adaptation, informational constraints, and interaction mechanisms, the framework enables the analysis of emergent outcomes such as price formation, coordination patterns, and market structure. The application to agricultural biomass markets illustrates how the framework can be operationalized in environments characterized by uncertainty, spatial heterogeneity, and evolving institutional conditions. The findings have important implications for economic research. They suggest that understanding market organization in complex environments requires methodological approaches that move beyond equilibrium-based representations and integrate behavioral realism with computational analysis. The proposed framework contributes to bridging the gap between complexity economics and applied research, offering a structured tool for analyzing economic behavior and organization in decentralized systems.