Prior research on competitive strategy in the presence of increasing returns suggests that early entrants can achieve sustained competitive advantage by pursuing Get Big Fast (GBF) strategies: rapidly expanding capacity and cutting prices to gain market share advantage and exploit positive feedbacks faster than their rivals. Yet a growing literature in dynamics and behavioral economics, and the experience of firms during the 2000 crash, raise questions about the GBF prescription. Prior studies generally presume rational actors, perfect foresight and equilibrium. Here we consider the robustness of the GBF strategy in a dynamic model with boundedly rational agents. Agents are endowed with high local rationality but imperfect understanding of the feedback structure of the market; they use intendedly rational heuristics to forecast demand, acquire capacity, and set prices. These heuristics are grounded in empirical study and experimental test. Using a simulation of the duopoly case we show GBF strategies become suboptimal when market dynamics are rapid relative to capacity adjustment. Under a range of plausible assumptions, forecasting errors lead to excess capacity, overwhelming the cost advantage conferred by increasing returns. We explore the sensitivity of the results to assumptions about agent rationality and the feedback complexity of the market. The results highlight the risks of incorporating traditional neoclassical simplifications in strategic prescriptions and demonstrate how disequilibrium behavior and bounded rationality can be incorporated into strategic analysis to form a dynamic, behavioral game theory amenable to rigorous analysis.
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