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 International Conference on Complex Systems (ICCS2007)

Technology and Market Spillovers in the Dynamics of Industry Evolution

Jeroen Struben
MIT Systems Dynamics Group

     Full text: Not available
     Last modified: July 5, 2007

Abstract
This research investigates market and technology dynamics in industries where learning and spillovers are significant. In examining technology introductions, the literature has made much progress in understanding the role of firm resources and their dynamics, the influence of environmental conditions, in particular firm competitive interactions. Much less has been studied by what process the evolutionary paths of the competitorsí resources, their products and the broader market environment shape each othersí trajectories, including failure and success. This paper focuses on one such mechanism, conditioning the flow of spillovers between technologies' systems of production and use. I develop a dynamic model of technology evolution with explicit and endogenous product innovation, learning and resource allocation. Resources may be devoted to improve knowledge through spillovers from other technologies. Technologies' value networks mature as adoption progresses, but may also benefit from penetration of related technologies. The market dynamics of entrants are characterized in terms of their degree of disruption and radicalism, conditioned by a range of industry factors. In plausible regimes the distribution of the likelihood breakthrough for a single entrant follows an inverse u-shape in the degree of radicalism. A key finding derives from multiple entrant analysis. An industry may breakaway to an exotic technology path through a cascading process in which relatively moderate technologies serve as scaffolding for increasingly exotic entrants that could not break through individually. Documented examples of empirical patterns that correspond with the simulations are abundant, but have not been formally associated with the underlying mechanisms discussed here. The character of the findings in this paper suggests useful approaches to understanding strongly path dependent trajectories of complex market technologies.







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