An agent-based approach to examine the ‘network knowledge advantage’ in open innovation networks: Firm openness and interorganizational network performance
In this paper we present the results of an agent-based model of open innovation, which suggest the network knowledge advantage underlying open interfirm networks of innovation, as opposed to an advantage arising from the interfirm network structure. To date, open innovation research has primarily been developed from firm-level case studies. Innovation network researchers have focused on cross-sectional studies of the strategic advantages of network structure and firm positioning as determinants of performance. However, the dynamics of learning and the accumulation of knowledge in open interorganizational networks of innovation and their effects on firm and system-level performance remain relatively unexplored, particularly given the impact of resource interdependencies that exist at the boundaries between firms. To address this important question, we explore the impact that open flows of knowledge have on productivity performance, given that firms must address the impact of interdependencies at the boundaries of such exchanges. In previous research we found that interdependencies can have a negative impact on productivity performance in relationally unstable networks. In the current model we find that a greater degree of firm openness towards interfirm exchange of knowledge has a positive impact on performance, and that even a small degree of firm openness towards building network level codified knowledge has a significant positive impact on performance. In conclusion, firm openness compensates for learning discontinuities that occur when network affiliations are loosely coupled. These findings on network-level knowledge dynamics have important implications for innovation theory and for the strategic management of collaborative innovation initiatives.