PROGRESS IN GEOGRAPHY ›› 2020, Vol. 39 ›› Issue (10): 1667-1676.doi: 10.18306/dlkxjz.2020.10.006

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Spatial structure of urban innovation network based on the Chinese unicorn company network

ZHOU Xiaoyan(), HOU Meiling*(), LI Xiaowen   

  1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
  • Received:2019-11-11 Revised:2020-05-14 Online:2020-10-28 Published:2020-12-28
  • Contact: HOU Meiling E-mail:zhouxiaoyan@whu.edu.cn;meilinghou@whu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(41571384);National Natural Science Foundation of China(71403193)

Abstract:

Unicorn company, a new term in today's business climate, is the integration of different types of innovations in the new era, and its internal relations and spatial organization reflect the pattern and characteristics of regional innovation networks. Consistent with the emerging entrepreneurship and the rapid development of the Internet, increasingly more unicorn companies appear in China, which provides an opportunity for us to catch a glimpse of China's innovation development through a new perspective. In this study, we used the ownership linkage model to map China's urban innovation network based on 164 Chinese unicorn companies' internal relations, and analyzed the spatial structure through the following social network analysis perspectives: urban hierarchy, association pattern, and city nodes. The "unicorn index" was developed as an indicator to evaluate the development and magnitude of a city's unicorn companies as well as its innovation environment and position in the network. Cities of high unicorn index values rank high in the urban innovation network hierarchy, which constitutes four tiers in a pyramid-shaped structure with 253 cities, only nine of which are in the top three tiers. Among them, Beijing, Shanghai, Hangzhou, and Shenzhen show their innovative activity and advanced development in the unicorn entrepreneurship. To analyze the association pattern, we calculated the network density, assortativity coefficient, and the degree correlation for the network. The results show that most cities are not closely linked with each other in this generally loose-association urban innovation network, while intensive connections only happen between the cities with high unicorn index, highlighting an intensive-connection diamond-shaped structure. To further examine each city node, we regard outdegree as its innovative influence and "power", indegree as its innovative attraction and "prestige", and eigenvector centrality as its connectivity. We found that Beijing and Shanghai still play leading roles in the innovation network, but Nanjing and Wuhan start to exhibit innovative attraction and potential. In conclusion, the development of urban innovation network is driven by four leading cities—Beijing, Shanghai, Hangzhou, and Shenzhen, showing a spatial polarization character. The network pattern highlights a diamond structure whose activity weakens from the east to the west. Cities having high unicorn index are strongly linked to each other and playing important roles while other cities enter the network by establishing links to those cities, shaping the core-periphery network structure. Moreover, those important cities enjoy power and prestige and have various influences in the innovation network. This study provides a new look into China's urban innovation network and some insights for policymakers to promote urban innovation. Also, the unicorn index can be considered in city innovation evaluation.

Key words: urban innovation network, unicorn company, unicorn index, social network analysis, China