Uncertain Learning Curves: Implications for First-Mover Advantage and Knowledge Spillovers

Abstract

The existence of a learning curve in which a firm’s costs decline with cumulative experience suggests that early entry provides learning opportunities that create advantage by reducing future costs relative to later entrants. While prior strategy research often assumes that learning curves are deterministic and known ex ante to firms, a substantial body of evidence suggests that learning curves are inherently uncertain. If there is uncertainty in the learning curve, then the taken-for-granted wisdom regarding the strategic implications of learning curves may over- or under-emphasize the value of early entry. We consider two forms of uncertainty — prospective (future costs) and contemporaneous (current costs). We demonstrate computationally that while prospective uncertainty in the learning curve enhances the benefits of early entry, contemporaneous uncertainty reduces these benefits. Further, we examine the implications of these findings for competition and learning curve spillovers between leader and laggard firms. Recognizing learning curve uncertainty highlights a novel form of spillovers that don’t affect expected cost, but rather affect uncertainty about cost. Our core insight is that when learning curve uncertainty is large relative to the expected learning rate, it is uncertainty, rather than expectations about this rate, that determines the extent of early mover advantage.