Can a region’s network location characteristics affect its innovation capability? Empirical evidence from China

Abstract

Purpose This study aims to explore the influence of a region’s network location characteristics and indirect connections on its innovation capability. The aim is to assist regions in different network locations to use innovation resources to improve their innovation capabilities more efficiently. Design/methodology/approach This paper represents the Chinese regional innovation network using the gravity model. A theoretical framework is developed to explore the relationships between a region’s innovation capability and its network location. Hypotheses are tested using hierarchical regressions. Findings First, this paper finds that a region’s network centrality can promote its innovation capability. Second, a structural hole can positively adjust the relationship between a region’s centrality and innovation capability. Third, a region’s indirect connections can inhibit its innovation capability while exhibiting a U-shaped relationship in moderating centrality and innovation capability. Originality/value This study uses a multi-index system to construct an innovation network covering 29 regions in China. This network represents the innovation cooperation and overall situation of innovation in China. The paper is one of the first attempts at investigating the relationship between regional network locations and innovation capability. It is also the first attempt at testing the influence of indirect connections on a region’s innovation capability. The findings provide a new perspective on the factors influencing regional innovation capacity and a new way for regions to improve their innovation capability.

Does large-scale research infrastructure affect regional knowledge innovation, and how? A case study of the National Supercomputing Center in China

“…Such cooperation can not only enhance the strength of existing collaborative interactions but also potentially form new cooperative relationships. The embedding of the innovation network structure can increase the centrality of the city in the network, which contributes to the attainment of more information and resource benefits (Han et al, 2021;Wen et al, 2021). Cross-regional cooperation connects innovation organizations with heterogeneous knowledge, which can alleviate the innovation reduction caused by homogeneous knowledge at the local level (Hazır et al, 2018).…”

“…This study focuses on whether the construction of NSC can affect the direct connection between NSC cities and other regions, as well as its embedding in the network structure, rather than focusing on the control of knowledge flow between nodes. Therefore, we select indicators that reflect urban centrality, including degree centrality and closeness centrality (Wang et al, 2014;Han et al, 2021).…”

“…In accordance with the social network theory, disparities in the positioning of individuals within a network can significantly influence the quantity and quality of information and resources they acquire, which leads to variations in innovative performance. Existing literature, based on diverse samples, has unveiled the augmented innovative performance associated with higher centrality in networks (Han et al, 2021;Wang et al, 2019). When entities occupy more central positions, they can engage in multidimensional technical collaborations and knowledge exchanges with various members.…”

Local context of local government participation in the innovation networks: Evidence from Poland

“…On the other hand, horizontal networks, which are most effective and function the best, are found in more developed regions [Lundvall, 1995]. In addition, there are relationships between a region's innovation capability and its network location [Han et al, 2020].…”

Production network: Application in China

“…As the industry division of the input–output table changes every year, we unify the industries in different years based on the construction methods in classical literature (Zhang et al, 2020; Zhu et al, 2020), to facilitate comparison over years. We first sort out 109 industries that exist in the “China Input–Output Table” in 2002 (122 sectors), 2007 (135 sectors), and 2012 (139 sectors).…”