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Generating Behavior in the University-Industry Collaboration Network: Based on the Configuration of Motifs

Abstract University-industry collaboration networks consist of heterogeneous subjects; in fact, the interactions among these subjects lead to the emergence of the complex characteristics of university-industry collaboration networks and even to the emergence of the networks themselves. Thus, understanding the behavior that generates university-industry collaboration networks is essential to their construction and optimization. To more fully comprehend this generating behavior, we considered a university-industry collaboration network in the ocean energy industry in China as a case study. Employing the motif analysis method, we analyze the network’s generating behavior from four perspectives: motif characteristics, motif classification, motif combination and motif clustering. Furthermore, we explore agents’ modes of adaptive collaboration — and the causes of such collaborations — and summarize the characteristics and modes of networks’ generating behavior. The results indicate that universities and industries tend to form highly stable and close cooperative relationships. The constraints of the network’s generating behavior — which influences the subjects’ interactions through relational and structural embeddedness — include asymmetric information, resource and cost constraints, risk aversion and geographical constraints. Our research presents the benefits of using the motif analysis method to study the network’s generating behavior and its implications in constructing and optimizing a university-industry collaboration network.