The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones

Abstract

In the context of “space of flows”, city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a large number of innovation resources. Here our report is to provide new ideas for improving the innovation capability of high-tech zones and accelerating the construction of Chinese high-quality innovation system. Here we take 142 cities with high-tech zones as research samples, and explore the characteristics and influencing factors of spatial network of city-based innovation correlation in China, through modified gravity modelsocial, network analysis and QAP analysis. The results show that city-based innovation network is not closely connected, the number of redundant connection channels is low efficiency, showing a four-level spatial pattern of “Z” shaped spindle. Among them, degree centrality of cities in eastern China is higher than that in the western region, the core cities in central China play a bridging role, and western remote cities are easily affected by related cities. Moreover, there are four innovation cohesion subgroups, including the northern hinterland subgroup, the eastern coastal subgroup, the southern subgroup and the western cooperation subgroup. Furthermore, the results of the influencing factors analysis show the differences in administrative level, economic development level, openness to the outside world, and investment in technology are conducive to the innovation association between cities, while the similarities in spatial adjacency and industrial structure will promote the strong innovation association between cities.

Evaluating economic efficiency of the national high-tech industrial development districts in the Yangtze River Delta by stochastic frontier analysis

“…Hefei HIDD ranks third or fourth through the whole period. This supports the previous findings that Suzhou and Hefei have more migrant flows of high-skilled workers in the YRD [ 8 , 28 , 47 ]. The poorest performed HIDDs are located mainly in North Jiangsu.…”

“…The high-tech industries have long been concentrated geographically but low intraregional specifications [ 7 ]. The spatial network of the innovation correlation is not connected very closely but eastern China is better than western China in terms of innovation connectedness [ 8 ]. It also suggests that the eastern coastal HIDDs become one of the innovation cohesion subgroups [ 7 , 8 ].…”

“…The spatial network of the innovation correlation is not connected very closely but eastern China is better than western China in terms of innovation connectedness [ 8 ]. It also suggests that the eastern coastal HIDDs become one of the innovation cohesion subgroups [ 7 , 8 ]. The comprehensive efficiency of national HIDDs is better than that of provincial HIDDs and economic-technological development zones (EDZs) in an underdeveloped province of China [ 9 ].…”

Knowledge Production in a Territorial Network of Organizations: Identifying the Determinants in the Case of Moroccan Technopole

“…In this sense, Gomes et al (2023) report that regional innovation inputs positively influence regional innovation outputs, which are represented by activities resulting from knowledge production in technopoles. According to Zhang et al (2023), innovation cohesion is considered an influencing factor of territorial network dynamics, which promotes a strong innovation association between the network's actors.…”