Is product life cycle theory a special case? Dominant designs and the emergence of market niches through coevolutionary-learning

Abstract

Product life cycle theory has been a key organizing principle in studies of technical innovation over the last 20 years and is promoted by leading management theorists as a tool for strategic decision making. This paper critically appraises the dominant design concept that lies at the heart of this theory. In so doing it seriously questions a basic premise adopted by numerous economists; that the dynamics of technological change can be understood through the examination of the technological artefact. We put forward an alternative explanation for the patterns of product innovation observed in infant industries. This alternative views technological innovation as a coupled, second-order learning system comprising a population of consumers and a population of firms. Within this approach the artefact is viewed in a quite different light. Rather than being an object in itself with its own internal drives and dynamics, it is a mediating device. The form of the mediating device alters over time due to changes in the external factors acting upon it; that is to say, its form changes as a consequence of the formation and development of user preferences through consumer learning and of the technological experimentation and beaming of firms. Turning specifically to the dominant design concept, we argue that this is but one possible outcome of the innovation system. It is shown that, while the system tends to converge towards a limited number of design configurations, there is no reason to expect it to stabilize around a single design. It may also stabilize through a process of market differentiation leading to the emergence of distinct niches. Observations drawn from the markets for cameras, road vehicles, amplification systems and personal computers support the contention that the dominant design outcome is a ‘special case’— a case of convergence to a single market niche. The theoretical and empirical analysis is formalized through a simulation model of the innovation system. The model is novel in a number of ways, particularly in the algorithms employed to model consumer and producer learning. Two key tests are conducted with this model. Firstly, we test whether a coupled learning system can indeed generate both single and multiple niche results. Secondly, we examine whether these results are consistent with the aggregate patterns of innovation that are observed. Having conducted these tests the paper proceeds, using the generated outputs of the model, to explore the different conditions under which single or multiple market niches can emerge.