Newcomers vs. incumbents: How firms select their partners for R\&D collaborations

This paper studies the selection of partners for R&D collaborations of firms both empirically, by analyzing a large data set of R&D alliances over 25 years, and theoretically, by utilizing an agent-based model of alliance formation. We quantify the topological position of a firm in the R&D network by means of the weighted k-core decomposition which assigns a coreness value to each firm. The evolution of these coreness values over time reconstructs the career path of individual firms, where lower coreness indicates a better integration of firms in an evolving R&D network. Using a large patent dataset, we demonstrate that coreness values strongly correlate with the number of patents of a firm. Analyzing coreness differences between firms and their partners, we identify a change in selecting partners: less integrated firms choose partners of similar coreness until they reach their best network position. After that, well integrated firms (with low coreness) choose preferably partners with high coreness, either newcomers or firms from the periphery. We use the agent-based model to test whether this change in behavior needs to be explained by means of strategic considerations, i.e. firms switching their strategy in choosing partners dependent on their network position. We find that the observed behavior can be well reproduced without such strategic considerations, this way challenging the role of strategies in explaining macro patterns of collaborations.