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

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  • Ivan Savin
  • Abiodun Egbetokun

Abstract

This paper extends the existing literature on strategic R&D alliances by presenting a model of innovation networks with endogenous absorptive capacity. The networks emerge as a result of bilateral cooperation over time between firms occupying different locations in the knowledge space. 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. Within different knowledge regimes, we examine the structure of networks that emerge and how firms perform within such networks. Our model replicates some stylised empirical results on network structure and the contingent effects of network position on innovative performance. We find networks that exhibit small world properties which are generally robust to changes in the knowledge regime. Second, subject to the extent of knowledge spillovers, certain network strategies such as occupying brokerage positions or maximising accessibility to potential partners pay off. Third and most importantly, absorptive capacity plays an important role in network evolution: firms with different network strategies indeed differ in the build-up of absorptive capacity.

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Bibliographic Info

Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers CEB with number 13-022.

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Length: 39 p.
Date of creation: 22 May 2013
Date of revision:
Publication status: Published by:
Handle: RePEc:sol:wpaper:2013/143871

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

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References

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  1. Fabrizio, Kira R., 2009. "Absorptive capacity and the search for innovation," Research Policy, Elsevier, vol. 38(2), pages 255-267, March.
  2. D. Blueschke & V. Blueschke-Nikolaeva & Ivan Savin, 2012. "New Insights Into Optimal Control of Nonlinear Dynamic Econometric Models: Application of a Heuristic Approach," Jena Economic Research Papers 2012-008, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  3. Victor Gilsing & Bart Noteboom & Wim Vanhaverbeke & Geert Duysters & Ad van Noord, 2006. "Network embeddedness and the exploration of novel technologies: technological distance, betweenness centrality and density," Working Papers 06-08, Eindhoven Center for Innovation Studies, revised Apr 2006.
  4. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
  5. Wuyts, S.H.K. & Colombo, M. & Dutta, S. & Nooteboom, B., 2005. "Empirical Tests of Optimal Cognitive Distance," Discussion Paper 2005-45, Tilburg University, Center for Economic Research.
  6. Robin Cowan & Nicolas Jonard & Jean-Benoit Zimmermann, 2007. "Bilateral Collaboration and the Emergence of Innovation Networks," Management Science, INFORMS, vol. 53(7), pages 1051-1067, July.
  7. Baum, Joel & Cowan, Robin & Jonard, Nicolas, 2009. "Network-independent partner selection and the evolution of innovation networks," MERIT Working Papers 022, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  8. Nooteboom, B. & Vanheverbeke, W.P.M. & Duysters, G.M. & Gilsing, V.A. & Oord van den, A,J,, 2005. "Optimal cognitive distance and absorptive capacity," Eindhoven Center for Innovation Studies (ECIS) working paper series 05.05, Eindhoven Center for Innovation Studies (ECIS).
  9. Uwe Cantner & Andreas Meder, 2007. "Technological proximity and the choice of cooperation partner," Journal of Economic Interaction and Coordination, Springer, vol. 2(1), pages 45-65, June.
  10. Joel A. C. Baum & Andrew V. Shipilov & Tim J. Rowley, 2003. "Where do small worlds come from?," Industrial and Corporate Change, Oxford University Press, vol. 12(4), pages 697-725, August.
  11. Abiodun Egbetokun & Ivan Savin, 2014. "Absorptive capacity and innovation: when is it better to cooperate?," Journal of Evolutionary Economics, Springer, vol. 24(2), pages 399-420, April.
  12. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
  13. Andersen Birgitte & Rossi Federica, 2010. "Recombinant Knowledge and Growth: The Case Of Icts," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201001, University of Turin.
  14. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
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