Knowledge-generating efficiency in innovation systems: The acceleration of technological paradigm changes with increasing complexity

Abstract

Time series of US patents per million inhabitants show cyclic structures which can be attributed to the different knowledge-generating paradigms that drive innovation systems. The changes in the slopes between the waves can be used to indicate efficiencies in the generation of knowledge. When knowledge-generating systems are associated with idem innovation systems, the efficiency of the latter can be modeled in terms of interactions among dimensions (for example, in terms of university-industry-government relations). The resulting model predicts an increase in efficiency with an increasing number of dimensions due to the effects of self-organization among them. The dynamics of the knowledge-generating cycles can be analyzed in terms of Fibonacci numbers; successive cycles are expected to exhibit shorter life cycles than previous ones. This perspective enables us to forecast the expected dates of future paradigm changes.

Innovation Search Scope, Technological Complexity, and Environmental Turbulence: A N-K Simulation

“…Similar to the concept of complex systems [26], technology is also composed of structured components. Knowledge complexity is the origin of technological complexity and is defined as the number and interaction of interdependent components, routines, individuals, and resources [27]. Simon [26] classifies knowledge as complex if it is composed of many elements that interact richly.…”

Smart management systems (Triple Helix model) in Waterloo, Canada

“…Developing the competitiveness of a city forces that city and its public-sector representatives invent new methods of management and use innovative thinking. Success of cities, according to Etzkowitz (2011); Etzkowitz and Leydesdorff (2000); Etzkowitz and Zhou (2007); Ivanova and Leydesdorff (2015); Leydesdorff and Ivanova (2016); Li, Zhan, and Lu (2016); Safiullin, Fatkhiev, and Grigorian (2014); and Syed and Omar (2016), concept, has to take into account new strategies of co-operation between academic institutions and local authorities, entrepreneurs and new graduates, focused on high-tech industries and start-up businesses. This trend is based on the principles of New Economic Geography (Krugman, 1994;Porter, 1998) and the new Theory of Growth (Lewis, 2003;Romer, 1990), which emphasize the importance of knowledge capital and smart technologies.…”

“Open innovation” and “triple helix” models of innovation: can synergy in innovation systems be measured?

“…; Braczyk et al 1998) from one perspective, while clustered in overlapping sets from another (e.g., sectors; Breschi et al 2003). Ivanova and Leydesdorff (2015) use the term "fractal manifold" to describe this fuzzy structure of innovation systems (Bathelt 2003;Carlsson 2006).…”