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An Information-Theoretic and Dissipative Systems Approach to the Study of Knowledge Diffusion and Emerging Complexity in Innovation Systems

机译：信息理论和耗散系统方法研究创新系统中的知识扩散和新兴复杂性

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The paper applies information theory and the theory of dissipative systems to discuss the emergence of complexity in an innovation system, as a result of its adaptation to an uneven distribution of the cognitive distance between its members. By modelling, on one hand, cognitive distance as noise, and, on the other hand, the inefficiencies linked to a bad flow of information as costs, we propose a model of the dynamics by which a horizontal network evolves into a hierarchical network, with some members emerging as intermediaries in the transfer of knowledge between seekers and problem-solvers. Our theoretical model contributes to the understanding of the evolution of an innovation system by explaining how the increased complexity of the system can be thermodynamically justified by purely internal factors. Complementing previous studies, we demonstrate mathematically that the complexity of an innovation system can increase not only to address the complexity of the problems that the system has to solve, but also to improve the performance of the system in transferring the knowledge needed to find a solution.
机译：本文应用信息论和耗散系统理论来讨论创新系统中复杂性的出现，这是由于复杂性适应了其成员之间认知距离的不均匀分布。通过一方面将认知距离建模为噪声，另一方面将与不良信息流相关的低效率建模为成本，我们提出了一种动力学模型，通过该模型，水平网络演变为分层网络，一些成员在寻求者和解决问题者之间的知识转移中成为中介。我们的理论模型通过解释如何通过纯粹的内部因素在热力学上证明系统的复杂性增加，从而有助于对创新系统的发展的理解。作为对先前研究的补充，我们在数学上证明了创新系统的复杂性不仅可以解决系统必须解决的问题的复杂性，而且可以提高系统在转移找到解决方案所需的知识方面的性能。 。

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