Authors: Qinchang GUI*, East China Normal University, Chengliang Liu, School of Urban and Regional Sciences, Institute for Global Innovation and Development, East China Normal University, Debin Du, School of Urban and Regional Sciences, Institute for Global Innovation and Development, East China Normal University
Topics: Economic Geography
Keywords: Network structure. Degree centrality. Structural holes. Small world. International scientific collaboration network
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Senate Room, Omni, West
Presentation File: No File Uploaded
There is consensus among scholars that social networks are important mechanism of knowledge spillovers. By occupying a central and advantageous network position in the collaboration network, it is easy for actors to access intangible external resources. However, empirical studies of the impact of network structure on knowledge production remain scarce. Based on copublication data from the Web of Science database (WoS) from 2000 to 2015, we construct eleven international scientific collaboration networks and empirically estimate the impacts of multiple network properties, comprehensively measured by degree centrality, structure holes, and small‐world quotient, on national knowledge output. Empirical results based on fixed effect negative binomial models suggest positive effects of the three facets of network properties, that is, higher degree centrality, structural holes, and small‐world quotient are beneficial for facilitating and improving national knowledge production, which in turn encourages international academic collaboration.