Abstract
Purpose of the paper : The aim of this study is to measure the impact of various dimensions of proximity to form innovation networks. Methodology : We use a novel statistical methodology for modelling networks based on a well-studied class of models called exponential-family random graph models. Findings : Results underline the importance of various forms of proximity in the formation of innovation networks and the potential of the novel methodology to study large and complex networks in innovation studies and R&D management. Research limits : The research is mainly quantitative and contributes to the debate measuring the role and importance of various forms of proximity in innovation networks. Further analysis of how firms choose their partners is needed. Moreover, the analysis should be expanded to other contexts and industries in order to be able to generalise results. Practical implications : The work points out managerial implications in innovation studies and R&D management in order to guide firms when choosing their partners and forming a network. Originality of the paper : The study contributes to the debate on innovation network literature and tests a novel methodology to analyse large and complex inter-organisational networks.
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