Emergence of innovation networks from R&D cooperation with endogenous absorptive capacity

Authored by Ivan Savin, Abiodun Egbetokun

Date Published: 2016

DOI: 10.1016/j.jedc.2015.12.005

Sponsors: German Research Foundation (Deutsche Forschungsgemeinschaft, DFG)

Platforms: C++ Microsoft Visual Studio MATLAB

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

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 dynamic cooperation between firms occupying different locations in the knowledge space. Partner selection is driven by absorptive capacity which is itself influenced by cognitive distance and R\&D investment allocation. Under different knowledge regimes, we examine the structure of networks that emerge and how firms perform within such networks. We find networks that exhibit small world properties which are generally robust to changes in the knowledge regime. Certain network strategies such as occupying brokerage positions or maximising accessibility to potential partners pay off, especially in `young' industries with limited involuntary but abundant voluntary spillovers. This particular result is driven by endogenous absorptive capacity. (C) 2016 Elsevier B.V. All rights reserved.

Tags

Evolution Collaboration knowledge Model Firm Relational embeddedness Small worlds Industries