Bilateral R&D Productivity and Supply Chain Networks

Abstract

We study R&D style influences in supply chain networks across internal, shared, and external resources. Collecting data for 1.27 million bilateral supply chain dyads from Bloomberg, we estimate R&D productivity from in-house, supply chain, and competitor investments. Our R&D productivity estimates for revenue generation outcomes reveal a large sample panel heterogeneity for productive and unproductive firms in each channel over time. Using a two-sided micro-econometric supply chain learning model, we find that all three types of R&D styles in terms of in-house, collaborative, and absorptive capabilities spread strongly in supply chain networks with negative cross-channel focus tradeoffs: increases in collaborative and absorptive partners reduce internal focus, and increases in self-centric partners reduce collaborative and absorptive efficiencies. We find that innovation barriers go down faster for agents and partners that share similar styles— partners who are successful at internal leadership produce stronger in-house leaders but less-productive supply chain collaborators and industry followers, and vice versa. Therefore, our findings imply that self-centric, collaborative, and imitative R&D styles clash to exert dominance over each other. Our findings provide important R&D productivity development and intellectual asset management insights for supply chain R&D practitioners while managing new, continuing, and expiring relationships.

Keywords: R&D styles, R&D productivity, supply chain innovation, R&D network selection