The identification of interlock groups in large corporate networks: convergent validation using divergent techniques

Abstract The present study attempts to assess the substantive and theoretical implications of using different analytical techniques to identify groups of highly interlocked corporations within large corporate networks. Specifically, it compares the interlock groups identified using direct factor analysis with those identified using hierarchical cluster analysis. A comparison of these two sets of empirical results suggests that these two analytical techniques yield surprisingly similar findings even though they employ disparate methodological rationales and computational algorithms. Nevertheless, some minor but significant differences in the results provided by these two techniques arise as a consequence of different assumptions implicit in these techniques concerning the possibility of overlap between interlock groups. Finally, the convergence of these two analyses confirms that interlock groups are concrete empirical aggregations within corporate networks which cannot be dismissed as the artifacts of particular analytical methodologies.