While developing the comprehensive index of Ego Network Quality (ENQ) Sebestyén and Varga (Ann Reg Sci, doi:10.1007/s00168-012-0545-x, 2013) integrates techniques mainly applied in a-spatial studies with solutions implemented in spatial analyses. Following the theory of innovation they applied a systematic scheme for weighting R&D in partner regions with network features frequently appearing in several (mostly non-spatial) studies. The resulting ENQ index thus reflects both network position and node characteristics in knowledge networks. Applying the ENQ index in an empirical knowledge production function analysis Sebestyén and Varga (Ann Reg Sci, doi: 10.1007/s00168-012-0545-x, 2013) demonstrate the validity of ENQ in measuring interregional knowledge flow impacts on regional knowledge generation. The aim of this chapter is twofold. First we show that ENQ is an integrated measure of network position and node characteristics very much resembling to the solution applied in the well-established index of eigenvector centrality. Second, we test the robustness of the weighting schemes in ENQ via simulation and empirical regression analyses.
CITATION STYLE
Sebestyén, T., & Varga, A. (2013). A novel comprehensive index of network position and node characteristics in knowledge networks: Ego network quality. In Advances in Spatial Science (Vol. 82, pp. 71–97). Springer International Publishing. https://doi.org/10.1007/978-3-319-02699-2_5
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