Industry Cluster Innovation Upgrading and Knowledge Evolution: A Simulation Analysis Based on Small-World Networks

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110316
Author(s):  
Di Ye ◽  
Linlin Zheng ◽  
Peixu He
Keyword(s):  
Simulation Analysis ◽  
Small World ◽  
Network Member ◽  
Small World Networks ◽  
Industry Cluster ◽  
Knowledge Evolution ◽  
Cluster Network ◽  
Cluster Evolution ◽  
Diffusion Simulation ◽  
Knowledge Absorption

This article focuses on the innovation and knowledge evolution of industry clusters. We examine the effects of the hub firm and the interaction of network member firms on the upgrading of the cluster. Our study is based on two patterns of knowledge learning and innovation, namely, STI (science, technology, and innovation) and DUI (doing, using, and interacting). This article adopts a knowledge diffusion simulation model to study the exchange of knowledge between cluster network actors in the context of small-world networks. The results indicate that we must pay close attention to the influence of hub enterprises on cluster evolution. Although hub companies may have certain innovation capabilities, if knowledge absorption problems among members are not properly resolved in the cluster network, the innovation performance of the local clusters is likely to be weakened, despite the success of the hub firm.

Networks

2018 ◽  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl
Keyword(s):  
Complex Systems ◽  
Complex Networks ◽  
Phase Diagrams ◽  
Community Detection ◽  
Network Science ◽  
Small World ◽  
Small World Networks ◽  
Multilayer Networks ◽  
Basic Vocabulary

Understanding the interactions between the components of a system is key to understanding it. In complex systems, interactions are usually not uniform, not isotropic and not homogeneous: each interaction can be specific between elements.Networks are a tool for keeping track of who is interacting with whom, at what strength, when, and in what way. Networks are essential for understanding of the co-evolution and phase diagrams of complex systems. Here we provide a self-contained introduction to the field of network science. We introduce ways of representing and handle networks mathematically and introduce the basic vocabulary and definitions. The notions of random- and complex networks are reviewed as well as the notions of small world networks, simple preferentially grown networks, community detection, and generalized multilayer networks.

Tracking sinks of atmospheric methane using small world networks

Chemosphere ◽  
2014 ◽  
Vol 117 ◽  
pp. 766-773 ◽  
Author(s):  
Chih-Sheng Lee ◽  
Pei-Jen Su
Keyword(s):  
Small World ◽  
Atmospheric Methane ◽  
Small World Networks

scholarly journals Multifractal analysis of eigenvectors of small-world networks

2021 ◽  
Vol 144 ◽  
pp. 110745
Author(s):  
Ankit Mishra ◽  
Jayendra N. Bandyopadhyay ◽  
Sarika Jalan
Keyword(s):  
Multifractal Analysis ◽  
Small World ◽  
Small World Networks

scholarly journals Critical exponents in coupled phase-oscillator models on small-world networks

2020 ◽  
Vol 102 (6) ◽  
Author(s):  
Ryosuke Yoneda ◽  
Kenji Harada ◽  
Yoshiyuki Y. Yamaguchi
Keyword(s):  
Critical Exponents ◽  
Small World ◽  
Phase Oscillator ◽  
Small World Networks ◽  
Coupled Phase Oscillator ◽  
Oscillator Models

Small‐World Networks Can Provide a New Tool to Study Diverse Systems

Physics Today ◽  
1998 ◽  
Vol 51 (9) ◽  
pp. 17-18 ◽  
Author(s):  
Gloria B. Lubkin
Keyword(s):  
Small World ◽  
Small World Networks

scholarly journals Dynamic rewiring in small world networks

2005 ◽  
Vol 72 (6) ◽  
Author(s):  
J. P. L. Hatchett ◽  
N. S. Skantzos ◽  
T. Nikoletopoulos
Keyword(s):  
Small World ◽  
Small World Networks

Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

2013 ◽  
Vol 110 (10) ◽  
Author(s):  
Ralph Stoop ◽  
Victor Saase ◽  
Clemens Wagner ◽  
Britta Stoop ◽  
Ruedi Stoop
Keyword(s):  
Small World ◽  
Small World Networks ◽  
Scale Free ◽  
Cortical Columns
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