The spatial-temporal complexity and dynamics of research collaboration: Evidence from 297 cities in China (1985–2016)

Xie, Qijun; Su, Jun

doi:10.1016/j.techfore.2020.120390

Cited by 19 publications

(10 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Both are innovative interactive networks. Previous social network research has explored cooperative relationships, information flows, and decisionmaking processes among countries, organizations, and individuals, respectively [29][30][31]. However, a comprehensive analysis of innovative social networks at these levels is lacking.…”

Section: Literature Review 21 Innovation Ecosystem and Its Compositio...mentioning

confidence: 99%

Exploring Innovation Ecosystem with Multi-Layered Heterogeneous Networks of Global 5G Communication Technology

Zhang,

Cui,

2024

Sustainability

View full text Add to dashboard Cite

This study explores the dynamics of emerging technology innovation ecosystems, viewing them as complex systems comprising social actors and knowledge artifacts engaged in innovation interactions. Employing a multilayer network perspective, we present a Social-Knowledge-Science-Technology (A-K-S-T) framework, examining both homogeneous and heterogeneous interactions among innovators and knowledge elements. Within this framework, we map out the technological landscape, identify ecological niches for specific actors and knowledge elements, and gauge knowledge proximity among innovators, revealing opportunities for collaboration and knowledge innovation. Using 5G technology as an illustrative example, key findings include the potential for innovation development in 5G, the need for enhanced collaboration among organizations in related technological fields, and the complementary nature of scientific and technological knowledge. This research contributes to innovation ecosystem literature, offering insights for management, governance, efficiency, and shared prosperity; meanwhile, it is a valuable reference for decision-makers to shape effective strategies.

show abstract

Section: Literature Review 21 Innovation Ecosystem and Its Compositio...mentioning

confidence: 99%

Exploring Innovation Ecosystem with Multi-Layered Heterogeneous Networks of Global 5G Communication Technology

Zhang,

Cui,

2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Although scholars have explored the polycentric structure of PUR using multiple types of functional linkages [18], there is a relative lack of research on the polycentricity of inter-city knowledge cooperation and its innovation networks [30]. In the knowledge economy era, the comprehensive competitiveness of PUR depends more on the level of innovation [6], and knowledge flows and their formation of innovation links are increasingly becoming the core of intercity relations [31] and affecting the evolution of the spatial structure [32]. Drawing on [33] idea of PUR as innovation incubator and hinge [34], propose the concept of knowledge polycentricity and analyze the knowledge flows within and outside city clusters and their impact on the evolution of spatial structure in the Yangtze River Delta.…”

Section: Innovation Network and Knowledge Polycentricmentioning

confidence: 99%

Exploring the Polycentric Structure and Driving Mechanism of Urban Regions From the Perspective of Innovation Network

Tang

Dou

2022

Front. Phys.

View full text Add to dashboard Cite

Polycentric city-regional development has become a buzzword for urban scholars and planners around the world. Inspired by the two critical characteristics of the polycentric urban region (PUR) as incubators and hinges of knowledge production, this study revealed the evolution of the polycentric structure and driving mechanism of PUR from the perspective of innovation network by using unique inter-city patent cooperation data. The results show that: 1) The innovation networks exhibit hierarchical and uneven characteristics, with the economic core cities becoming incubators and hinges of innovation and dominating the development of innovation networks. 2) There is compatibility between morphological polycentricity and functional polycentricity in PURs, but there are also differences. Although the morphological polycentricity of three PURs has improved, functional polycentricity is underdeveloped. 3) The geographic, institutional, institutional, and cultural proximity play the facilitating role for inter-city knowledge flows and their polycentric enhancement, but city attributes such as population size have a lower impact. Our study is believed to renew the knowledge polycentricity conceptualization and enlighten the evolution of innovation network.

show abstract

“…As China aims to be an innovation powerhouse globally and has adopted a series of policies to promote cross-region innovation collaboration, it provides an ideal context for studying regional innovation collaboration in developing countries. In recent years, some researchers have chosen to study the structure and development of Chinese innovation networks at the province or city level, but not at a relational level between these spatial entities (Lu and Huang, 2012;Ma et al, 2015;Sun and Cao, 2015;Sun, 2016;Xie and Su, 2021;Yao and Li, 2022). However, only a few studies explored the determinants of cross-region innovation collaboration, usually just focusing on specific industries and regions (Ma et al, 2014;Li et al, 2015;Dong et al, 2021;Liu et al, 2021), lacking a city-level perspective (Scherngell and Hu, 2011;Pan et al, 2020), or ignoring the longterm evolvement of the mechanism (Jiang et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Drivers for Inter-city Innovation Networks Across Chinese Cities: Modelling Physical Versus Intangible Effects

Gao,

Scherngell,

Neuländtner

2024

Chin. Geogr. Sci.

View full text Add to dashboard Cite

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity. In the recent past, a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts. However, existing research mainly focuses on physical effects, such as geographical distance and high-speed railway connections. These studies ignore the intangible drivers in a changing environment, the more digitalized economy and the increasingly solidified innovation network structure. Thus, the focus of this study is on estimating determinants of innovation networks, especially on intangible drivers, which have been largely neglected so far. Using city-level data of Chinese patents (excluding Hong Kong, Macao, and Taiwan Province of China), we trace innovation networks across Chinese cities over a long period of time. By integrating a measure on Information and Communications Technology (ICT) development gap and network structural effects into the general proximity framework, this paper explores the changing mechanisms of Chinese innovation networks from a new perspective. The results show that the structure of cross-region innovation networks has changed in China. As mechanisms behind this development, the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity, such as geographical distance. Since digitalization and coordinated development are the mainstream trends in China and other developing countries, these countries’ inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

show abstract

The spatial-temporal complexity and dynamics of research collaboration: Evidence from 297 cities in China (1985–2016)

Cited by 19 publications

References 49 publications

Exploring Innovation Ecosystem with Multi-Layered Heterogeneous Networks of Global 5G Communication Technology

Exploring Innovation Ecosystem with Multi-Layered Heterogeneous Networks of Global 5G Communication Technology

Exploring the Polycentric Structure and Driving Mechanism of Urban Regions From the Perspective of Innovation Network

Drivers for Inter-city Innovation Networks Across Chinese Cities: Modelling Physical Versus Intangible Effects

Contact Info

Product

Resources

About