Emergence of Innovation Networks from R$\&$D Cooperation with Endogenous Absorptive Capacity

Ivan Savin^* and Abiodun Egbetokun

This paper extends the existing literature on strategic R$\&$D alliances by presenting a model of innovation networks with endogenous absorptive capacity. Social capital is ignored, and firms ally purely on the basis of knowledge considerations. Partner selection is driven largely by absorptive capacity which is itself influenced by cognitive distance and investment allocation between inventive and absorptive R$\&$D. Cognitive distance between firms changes as a function of the intensity of cooperation and innovation. Networks emerge as a result of bilateral cooperations over time between firms occupying different locations in the knowledge space. Under varying network-independent characteristics of the knowledge space, we examine the structure of networks that emerge and how firms perform within such network structures. Our model replicates well-founded empirical results on network structure and the contingent effects of network position on firms' performance. In particular, we find, first, that the networks exhibit small world properties which are generally robust to changes in the knowledge regime. Second, certain network strategies such as occupying brokerage positions or maximising accessibility to potential partners pay off. This naturally varies depending on the extent of knowledge spillovers. Third and most importantly, firms with different network strategies indeed differ in their absorptive capacities.

Mathematics Subject Classification: 37H10 11Y16

Keywords: absorptive capacity; agent-based modeling; cognitive distance; dynamics; innovation; knowledge spillovers; networks

Minisymposion: Computational Optimization Methods in Statistics, Econometrics and Finance