Abstract
This paper applies chaos theory to innovation processes, highlighting nonlinear behavior and temporal dynamics in the process of substitution of old and established technologies with the newly created ones. We employed two independent but complementary mathematical tools, local Hurst exponent (LHE) and local Lyapunov exponent (LLE), to develop our model of analysis and define the edge of chose. To illustrate our ideas, we analyzed the development of printers during 1976~2012 period using patent application data. The results of the chaotic models were matched against the profiles of patent citation data to provide a triangulated explanation. We discuss implications for chaos theory, innovation studies, research methods, as well as managerial practices.
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