A Behavioral Analysis of Learning Curve Strategy (Classic Reprint) - Tapa blanda

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In this paper we show that relaxing the assumptions of instantaneous market clearing and perfect foresight leads, in a variety of plausible circumstances, to competitive dynamics significantly different from those predicted by much of the existing literature. We begin with a review of the literature on strategy in the presence of learning curves. We then develop a model in which the assumptions of market clearing and rationality are replaced by a disequilibrium, behavioral framework in which firms face lags in adjusting capacity and use boundedly rational decision heuristics to set prices and forecast demand. We use the model to explore the impact of an aggressive leaming-curve strategy in a variety of environments.

When the dynamics of the market are sufficiently slow, delays in information acquisition, decision making, and system response are sufficiently short, and the cognitive demands on the firms are sufficiently low, behavioral theory yields predictions observationally indistinguishable from those of equilibrium models. However in more dynamic environments, in which boundedly rational forecasting techniques become less accurate, the aggressive learning curve strategies prescribed in the game theory literature become inferior, as aggressive expansion leads to excess capacity. We close with implications for the study of strategic competition in general, arguing that the neoclassical assumptions of equilibrium and rationality may in many realistic circumstances prove to be a dangerous guide to action and a weak basis for empirical research.

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