Social network analysis attracts increasing attention in economic geography. We claim social\ud network analysis is a promising tool for empirically investigating the structure and evolution of\ud inter-organizational interaction and knowledge flows within and across regions. However, the\ud potential of the application of network methodology to regional issues is far from exhausted.\ud The aim of our paper is twofold. The first objective is to shed light on the untapped potential of\ud social network analysis techniques in economic geography: we set out some theoretical\ud challenges concerning the static and dynamic analysis of networks in geography. Basically,\ud we claim that network analysis has a huge potential to enrich the literature on clusters,\ud regional innovation systems and knowledge spillovers. The second objective is to describe\ud how these challenges can be met through the application of network analysis techniques,\ud using primary (survey) and secondary (patent) data. We argue that the choice between these\ud two types of data has strong implications for the type of research questions that can be dealt\ud with in economic geography, such as the feasibility of dynamic network analysis
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