Bilateral Collaboration and the Emergence of Innovation Networks

By Robin Cowan, Nicolas Jonard, Jean-Benoit Zimmermann. Management Sciences, 2007

311 citations recorded by the source corpus.

In this paper, we model the formation of innovation networks as they emerge from bilateral decisions. In contrast to much of the literature, here firms only consider knowledge production, and not network issues, when deciding on partners. Thus, we focus attention on the effects of the knowledge and information regime on network formation. The effectiveness of a bilateral collaboration is determined by cognitive, relational, and structural embeddedness. Innovation results from the recombination of knowledge held by the partners to the collaboration, and its success is determined in part by the extent to which firms' knowledge complement each other. Previous collaborations (relational embeddedness) increase the probability of a successful collaboration, as does information gained from common third parties (structural embeddedness). Repeated alliance formation creates a network. Two features are central to the innovation process: how firms pool their knowledge resources, and how firms derive information about potential partners. When innovation is decomposable into separate subtasks, networks tend to be dense; when structural embeddedness is important, networks become cliquish. For some regions in this parameter space, small worlds emerge.

Subfields: Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/3d28a609bef40bed3c7c514dd65f6b33a64741cb

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In Management Science and Operations Research

  1. Ron A. Boschma
  2. Pierre-Alexandre Balland
  3. Mathijs de Vaan
  4. Yem Yvonne Kirkels
  5. Geert Duysters
  6. Koen Frenken
  7. Rahul C. Basole
  8. J. Bergh

In Strategy and Management

  1. Ron A. Boschma
  2. Pierre-Alexandre Balland
  3. Koen Frenken
  4. Yem Yvonne Kirkels
  5. Mathijs de Vaan
  6. Geert Duysters
  7. Rahul C. Basole
  8. E. Stam

Citations in the corpus