Evolutionary networks of interurban technological collaboration across Chinese city-regions

ABSTRACT

Urban agglomeration has the function of being an incubator for innovation. Previous studies have only focused on the output of innovation, ignoring the knowledge cooperation and exchange between cities, which is an important embodiment of the incubation. Compared with scientific cooperation, technical cooperation is more experimental and application oriented, requires more face-to-face communication, and is more sensitive to distance. In this paper co-patent data were selected to show the development and differences of intercity technological cooperation networks within Chinese urban agglomerations. The results show that the technical cooperation network within Chinese urban regions has generally developed rapidly in the past decade, especially those in eastern China, which have become the closest urban regions in China’s technical cooperation.

KEYWORDS:

• intercity networks
• regional innovation
• urban region
• technological collaboration
• patent co-inventorship
• network evolution
• China

JEL CLASSIFICATIONS:

• O3

Knowledge is geographically unevenly distributed, with cities often seen as the key territorial unit for innovation activities (Florida et al., 2017). Connections to external knowledge resources tend to strengthen the local routines of innovation agents in a given city due to the complementarity and diversity of internal and external knowledge. Moreover, regional collaborations in research and development (R&D) increase opportunities for knowledge spillover and positively affect the regional innovation (Broekel et al., 2017). These principles apply to both scientific and technical knowledge; however, these two types of knowledge are characterized by markedly different flow patterns (Maggioni et al., 2017). Whilst many studies have addressed the issue of inter-city scientific collaboration networks (Cao et al., 2021), relatively few have paid attention to technical collaboration. Unlike scientific knowledge, which focuses on explaining specific phenomena and patterns, technological knowledge is related to applied knowledge generation and focuses on the development of marketable and industrial research activities (Makri et al., 2010). It is developed, moreover, processed through learning-by-doing or learning-by-using.

China has seen a rapid increase in the production of technological knowledge over the past decade, and in 2019 for the first time China became the world’s leading country in terms of international patent applications (WBG & DRC, 2019). Most of the production of technological knowledge in China takes place in urban regions: between 2017 and 2019, the 19 urban regions defined in the Atlas of Urban Agglomeration in China (Fang, 2020) accounted for 92.48% of China’s total publications in the Global Patent Database. The innovation development strategies of Chinese governments at all levels have been successful in promoting the growth of technological knowledge in the country, which also has stimulated inter-city technical collaboration, especially in economically developed city-regions.

Figure 1 shows the evolution of the inter-city technological collaboration networks within 19 Chinese city-regions over the past decade. The networks are constructed based on the frequency of the co-occurrence of cities in technological publications, using data mined from the global patent database IncoPat. The average of the three years following the implementation of the two national innovation strategies (2007–09 and 2017–19) was chosen as the study period in order to examine these evolutionary trends. The size of the nodes represents the number of collaborative links a city has, while the width and colour of the edges represent the number of interurban collaborations that exist between two cities.

Figure 1. Interurban technological collaboration networks across 19 Chinese city-regions, 2007–09 and 2017–19.

Note: YRD, Yangtze River Delta; BTH, Beijing–Tianjin–Hebei; PRD, Pearl River Delta; MYR, Middle Yangtze River; CHC, Chengdu–Chongqing; SDP, Shandong Peninsula; WTS, West Taiwan Strait; CSL, Central–Southern Liaoning; HAC, Harbin–Changchun; CPL, Central Plain; GZP, Guanzhong Plain; CSX, Central Shanxi; LAX, Lanzhou–Xining; HBY, Hubaoe Yu; GXB, Guangxi Beibu Gulf; CYN, Central Yunnan; CGZ, Central Guizhou; NYR, Ningxia Yellow River; and TSM, Tianshan Mountains. Cities with labels are capital cities; cities without labels are prefectural cities.

From the comparison of the two stages, three main features emerge:

• The internal technological collaboration within city-regions, including the urban degree centrality and number of inter-city cooperative links in the network, has grown markedly. The highest value of urban degree centrality in the early part of the study period reflected that of the fourth level in the second part of the period, and with the highest value for inter-city collaboration in the early part also dropping to the fourth or fifth level in the latter part. With the increase of the order of magnitude of the technical collaboration network present in the eastern city-regions, western city-region networks have also begun taken initial shape.

• Whether in the former or latter stage, the degree of technological network development in the eastern city-regions was found to be much higher than that of the central and western regions, a significant regional gap that further widened over the study period. For example, while city-regions on the eastern coast tend to include a greater number of high-level cities, the central and western city-regions lack the drive of such high-level cities. The degree centrality and connections of high-level cities increased more than 30 times between the first and second parts of the study period. The eastern metropolitan region remained a high technological growth pole in China.

• The political orientation of strong technology centres in the network is still evident (Andersson et al., 2014). Municipalities and provincial capitals have strong network status, dominating the development of the technical collaboration network. However, compared with the results obtained with respect to the scientific collaboration network (Cao et al., 2021), a number of prefectural cities with a not-so-strong political status have emerged with higher network status, including Suzhou and Ningbo in the Yangtze River Delta, Shenzhen and Dongguan in the Pearl River Delta, and Baoding and Handan in Beijing–Tianjin–Hebei. Whether this is related to the deepening of the industrial division of labour in cities at different levels within the city-regions and technological knowledge is closely tied to industrial development is worth further study.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 41971209]; the Third Xinjiang Scientific Expedition Program [grant number 2021xjkk0900]; and the Major Program of the National Social Science Foundation of China [grant number 21&ZD107].