AN INVENTORY MODEL FOR ADVANCED MATHEMATICAL MODELING ACROSS MULTIPLE INTERCONNECTED MARKETS
DOI:
https://doi.org/10.29121/granthaalayah.v14.i2.2026.6808Keywords:
Multimarket, Modeling, Equilibrium, Optimization, Networks, Competition, Dynamics, SustainabilityAbstract [English]
This study presents a comprehensive framework for advanced mathematical modeling across multiple interconnected markets, highlighting the importance of capturing interdependencies among demand, supply, pricing, and strategic interactions. Unlike traditional single-market analyses, multi-market modeling recognizes that economic and financial systems operate as complex, interlinked structures where changes in one market influence outcomes in others. The paper reviews key theoretical foundations, including multi-market equilibrium theory, partial and general equilibrium models, two-sided and multi-sided market structures, agent-based modeling, and optimal control approaches. These models enable the analysis of competitive behavior, cross-market spillovers, trade flows, inventory coordination, and policy interventions within integrated market environments. Special emphasis is placed on dynamic and nonlinear modeling techniques that account for uncertainty, behavioral heterogeneity, and network effects. Mathematical formulations such as Walrasian equilibrium conditions, cross-elasticity demand systems, inter-regional trade equations, platform-based network utility functions, and optimal control structures are systematically discussed. The paper also explores the growing role of computational methods, including simulation, machine learning integration, and data-driven optimization, in enhancing the scalability and predictive accuracy of multi-market models. Despite the strong theoretical development, the paper identifies a major research gap in empirical validation and real-world calibration of these models. To address this limitation, future research directions emphasize large-scale data integration, dynamic adaptive modeling, interdisciplinary collaboration, and the inclusion of external shocks such as regulatory changes and geopolitical risks. The proposed modeling frameworks offer valuable decision-support tools for policymakers, firms, and researchers operating in volatile and interconnected market systems.
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