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This paper examines how industry changes through the nonlinear view of chaos theory. Chaos theory implies that a dynamic system is nonlinear. Accordingly, we developed a triangulated analysis constituted by five mathematical approaches, including the BDS test, Hurst exponent, correlation dimension, Lyapunov exponent, and local Lyapunov exponent, to explore industry change as a nonlinear dynamic system. Empirically, we choose to compare the semiconductor industry and the biotechnology industry, using data collected from the Philadelphia Semiconductor Index and the NASDAQ Biotechnology Index. We found and confirmed that both industries evolved in a nonlinear manner, with the semiconductor industry being less unpredictable, more path-dependent, more sensitive to initial conditions, and has more time-paced incremental innovations than the biotechnology industry. We then complement this analysis with historical case studies that in turn leads us to argue that such differences have much to do with the inherent nature of the industries themselves. While the presence of Moore's Law as a roadmap projects the semiconductor industry into a more predictable path, the distributed nature of biotechnology coupled with the lack of a dominant technology directs the industry towards a system with greater volatilities and nonlinearities. [ABSTRACT FROM AUTHOR]

This paper aims to enrich our understanding of punctuated equilibrium in technological change, which argues that technology evolves through a relatively long period of stability and continuity that is interrupted and punctuated by a relatively short burst of discontinuous, radical change. Most past literature has paid little attention to the embedded knowledge flow in technological change. To address this gap, a conceptual framework is exhibited to summarize our idea. The key-route main path analysis approach is used to construct the knowledge flow in punctuated equilibrium. Empirically, the thermal inkjet printhead is chosen as the research target, and patent data from USPTO were collected and used. We found that thermal inkjet printheads experienced three distinct phases of technological continuities, each of which is a cyclic divergent-convergent knowledge flow initiated by a breakthrough centering around a significant, prioritized technical problem. One knowledge cycle is to shape a distinct knowledge base and a dominant design. In addition, the short burst of punctuation between two sequential knowledge cycles is exactly where a technological discontinuity arises, fundamentally transforming the existing knowledge base to solve emerging problems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]