Too big to see: exploring proxies of structure in a real large-scale university-industry cooperation network

Abstract

We investigate static and dynamic topologies of a 2-mode real world university-industry cooperation network. Due to its large size and complex structure, we choose to use statistical proxies for this goal. Among the findings, we shall call attention to the rank-size distribution of the firm node degrees with power law signature log-linear behavior. Which invokes hints of a complex network architecture, as a counterpoint to the random case. We compare furthermore the rank-size distributions of both modes with other real-world 2-mode large-scale networks and draw parallels for their causes. Moreover, we investigate structural change in the network by computing Robins-Alexander clustering coefficients in a rolling window fashion in order to capture topological change in the network temporal evolution. Findings suggest that network stability is achieved after a short transition phase of high clustering and cross-correlation.

5 pages, 3 figures, submitted to the 5th Geography of Innovation Conference (GEOINNO2020)