Abstract
We model firms’ output decisions in a repeated duopoly framework, focusing on three interrelated issues: (1) the role of learning in the adjustment process toward equilibrium, (2) the role of organizational structure in the firm's decision making, and (3) the role of changing environmental conditions on learning and output decisions. We characterize the firm as a type of artificial neural network, which must estimate its optimal output decision based on signals it receives from the economic environment (which influences the demand function). Via simulation analysis we show: (1) how organizations learn to estimate the optimal output over time as a function of the environmental dynamics, (2) which networks are optimal for each level of environmental complexity, and (3) the equilibrium industry structure.