### Abstract

We introduce the model of knowledge spillover on networks. Knowledge spillover is a major source of economic growth; and is a representative externality in economic phenomena. We show that the model has the following four characteristics: (1) the long-run growth rate is not relevant to the mean degree, but is determined by the mean degree of the nearest neighbors; (2) the productivity level of a firm is proportional to the degree of the firm; (3) the long-run growth rate increases with the increasing heterogeneity of the network; and (4) of three representative networks, the largest growth rate is in scale-free networks and the least in regular networks.

Original language | English |
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Pages (from-to) | 1207-1214 |

Number of pages | 8 |

Journal | Physica A: Statistical Mechanics and its Applications |

Volume | 462 |

DOIs | |

Publication status | Published - 2016 Nov 15 |

### Keywords

- Complex networks
- Knowledge spillover
- Network heterogeneity
- Scale-free networks

### ASJC Scopus subject areas

- Statistics and Probability
- Condensed Matter Physics

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## Cite this

Konno, T. (2016). Knowledge spillover processes as complex networks.

*Physica A: Statistical Mechanics and its Applications*,*462*, 1207-1214. https://doi.org/10.1016/j.physa.2016.06.124