Co-evolution of the global research collaboration network and the performance of nations in science and technology

Abstract: Researchers have long suspected that international research collaboration (IRC) and scientific and technological (S&T) performance are subject to reciprocal causality, yet the endogenous co-evolution of these twin phenomena has yet to be tested by large-scale empirical analysis. This study tests IRC network effects on national research performance and vice versa simultaneously using a longitudinal co-evolution model on three decades of global network and national performance data. Stochastic actor oriented models (SAOM) are used to analyze data on 166 countries from 1993 to 2022. Yearly IRC networks are constructed from Web of Science's XML database, and performance data are gathered from Elsevier's fractional field-weighted citation index (FWCI). The models also account for geographic, economic, demographic, and political factors, as well as endogenous network processes. The results provide support for reciprocal co-evolution. However, notably, geographic distance appears to moderate the interaction between research performance and network dynamics, suggesting researchers may rely more on visible performance metrics when selecting geographically distant collaborators. This finding points to the role of citation based performance metrics as a signaling mechanism for collaborator selection.