Abstract
In recent years, the structure of incubation networks has attracted much attention. However, the intricacy of network has limited the discussions on its structure and dynamics. Information theory is employed as a model independent approach, which is capable of overcoming these obstacles. Information flows between different regions are calculated with the help of the transfer entropy methodology. Moreover, corresponding incubation networks are constructed over two periods. Thereafter, local transfer entropy is calculated for analysing how the structure of networks is changing with time. The results obtained are presented as follows. Firstly, the adjacent geographical location is the key factor in the formation of region incubation networks and six region incubation networks are formed in China; Secondly, network-level in different regions exhibits a serious imbalance; Finally, the policy significantly contributes to the dynamics of region incubation networks. The key findings revealed in the paper extend support to the governments and local authorities in shaping their prospective policies for not only the incubation industry, but also the entrepreneurs, and development of the region economy.
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Appendix
Appendix
The name and number of the 41 Chinese regions
Region | Number | Region | Number |
---|---|---|---|
Beijing | 1 | Guizhou | 23 |
Tianjin | 2 | Yunnan | 24 |
Hebei | 3 | Xizang | 25 |
Shanxi | 4 | Shanxi | 26 |
Neimenggu | 5 | Gansu | 27 |
Liaoning | 6 | Qinghai | 28 |
Jilin | 7 | Ningxia | 29 |
Heilongjiang | 8 | Xinjiang | 30 |
Shanghai | 9 | Dalian | 31 |
Jiangsu | 10 | Ningbo | 32 |
Zhejiang | 11 | Qingdao | 33 |
Anhui | 12 | Xiamen | 34 |
Fujian | 13 | Shenzhen | 35 |
Jiangxi | 14 | Wuhan | 36 |
Shandong | 15 | Guangzhou | 37 |
Henan | 16 | Xian | 38 |
Hubei | 17 | Chengdu | 39 |
Hunan | 18 | Zhengzhou | 40 |
Guangdong | 19 | Nanjing | 41 |
Guangxi | 20 | ||
Chongqing | 21 | ||
Sichuan | 22 |
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Li, H., Tang, Y. Network Structure and Dynamics of Chinese Regional Incubation. Netw Spat Econ 19, 1173–1197 (2019). https://doi.org/10.1007/s11067-019-09446-9
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DOI: https://doi.org/10.1007/s11067-019-09446-9