### 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 |
---|---|

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 |

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### Keywords

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

### ASJC Scopus subject areas

- Statistics and Probability
- Condensed Matter Physics

### Cite this

*Physica A: Statistical Mechanics and its Applications*,

*462*, 1207-1214. https://doi.org/10.1016/j.physa.2016.06.124

**Knowledge spillover processes as complex networks.** / Konno, Tomohiko.

Research output: Contribution to journal › Article

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

}

TY - JOUR

T1 - Knowledge spillover processes as complex networks

AU - Konno, Tomohiko

PY - 2016/11/15

Y1 - 2016/11/15

N2 - 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.

AB - 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.

KW - Complex networks

KW - Knowledge spillover

KW - Network heterogeneity

KW - Scale-free networks

UR - http://www.scopus.com/inward/record.url?scp=84978630606&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84978630606&partnerID=8YFLogxK

U2 - 10.1016/j.physa.2016.06.124

DO - 10.1016/j.physa.2016.06.124

M3 - Article

VL - 462

SP - 1207

EP - 1214

JO - Physica A: Statistical Mechanics and its Applications

JF - Physica A: Statistical Mechanics and its Applications

SN - 0378-4371

ER -