Corporations across the world are highly interconnected in a large global network of corporate control. This paper investigates the global board interlock network, covering 400,000 firms linked through 1,700,000 edges representing shared directors between these firms. The main focus is on the concept of centrality, which is used to investigate the embeddedness of firms from a particular country within the global network. The study results in three contributions. First, to the best of our knowledge for the first time we can investigate the topology as well as the concept of centrality in corporate networks at a global scale, allowing for the largest cross-country comparison ever done in interlocking directorates literature. We demonstrate, among other things, extremely similar network topologies, yet large differences between countries when it comes to the relation between economic prominence indicators and firm centrality. Second, we introduce two new metrics that are specifically suitable for comparing the centrality ranking of a partition to that of the full network. Using the notion of centrality persistence we propose to measure the persistence of a partition’s centrality ranking in the full network. In the board interlock network, it allows us to assess the extent to which the footprint of a national network is still present within the global network. Next, the measure of centrality ranking dominance tells us whether a partition (country) is more dominant at the top or the bottom of the centrality ranking of the full (global) network. Finally, comparing these two new measures of persistence and dominance between different countries allows us to classify these countries based the their embeddedness, measured using the relation between the centrality of a country’s firms on the national and the global scale of the board interlock network.
Centrality has long been a basic concept in the study networks of interlocking directorates, in the beginning focusing mainly on degree centrality. As social network analysis gained more popularity, new centrality measures were proposed and applied to understand networks of interlocking directorates @cite_18 , for example to see differences between banks and nonbanks @cite_39 . In @cite_11 it is argued that the function of monitoring and the provisioning of resources of well-connected board has an effect on firm performance. However, when it comes to the precise relationship of firm performance and topological board interlock network measurements, the results are diverse. Correlations between centrality and economic performance are frequently demonstrated, but differ in strength across studies. For example, in @cite_26 it was shown that higher node centrality in the United States results in better boardroom performance, measured using a number of economic performance indicators. In @cite_30 , it was found that in the United Kingdom, the connectedness of directors and thus their boards is positively associated with firm performance, and a similar conclusion is drawn in @cite_2 for director networks.
@cite_30 @cite_18 @cite_26 @cite_39 @cite_2 @cite_11
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We use measures of vertex centrality to examine interlocking directorates and their economic effects in Italy. We employ centrality measures like degree, eigenvector centrality, betweenness, and flow betweenness, along with the clustering coefficient. We document the existence of a negative relationship between both degree and eigenvector centrality and firm value. Betweenness and flow betweenness, on the other hand, are not associated with lower firm valuations. We argue that these differences derive from the different properties of these measures: while degree and eigenvector centrality measures the influence and the power of the connections, betweenness and flow betweenness are proxies for the volume of information that passes between the nodes. This result is robust with respect to the use of both stock market and operating performance measures, as well as several controlling variables. I There is a terminological difficulty to be noted here. "Centrality" has both a generic and a particular meaning in this paper. Generically, "centrality" refers to any of three intuitive conceptions: degree (connectedness), closeness, and betweenness (Freeman, 1979). In its particular sense, "centrality" refers to any variation of a measurement technique introduced by Phillip Bonacich (1972a, 1972b) and further elaborated in (1975), Mariolis (1975), and Mariolis, Schwartz, and Mintz (1979). When using it in this latter sense, we generally refer to "centrality scores," or to "directional" and "nondirectional" centrality. In other cases, the context should make clear which of the two meanings we intend. This paper addresses a series of empirical, methodological, and theoretical questions raised by examining the reliability and stability of centrality in corporate interlock networks. Data on the interlocking directorates of 1094 large U.S. corporations in 1962, 1964, and 1966 are analyzed with a test-retest simultaneous equation model. The results confirm the common, but little tested, assumptions that centrality measures are highly reliable and stable. Further, we find that, of three measures examined (number of interlocks, nondirectional centrality, and directional centrality), number of interlocks is slightly more reliable or stable than the other two. Finally, the results show that the centrality of banks is more stable than the centrality of nonbanks. We conclude with a discussion of the implications of these findings.* Centrality has revealed crucial for understanding the structural properties of complex relational networks. Centrality is also relevant for various spatial factors affecting human life and behaviors in cities. Here, we present a comprehensive study of centrality distributions over geographic networks of urban streets. Five different measures of centrality, namely degree, closeness, betweenness, straightness and information, are compared over 18 1-square-mile samples of different world cities. Samples are represented by primal geographic graphs, i.e., valued graphs defined by metric rather than topologic distance where intersections are turned into nodes and streets into edges. The spatial behavior of centrality indices over the networks is investigated graphically by means of color-coded maps. The results indicate that a spatial analysis, that we term multiple centrality assessment, grounded not on a single but on a set of different centrality indices, allows an extended comprehension of the city structur... The concept of centrality is often invoked in social network analysis, and diverse indices have been proposed to measure it. This paper develops a unified framework for the measurement of centrality. All measures of centrality assess a node's involvement in the walk structure of a network. Measures vary along four key dimensions: type of nodal involvement assessed, type of walk considered, property of walk assessed, and choice of summary measure. If we cross-classify measures by type of nodal involvement (radial versus medial) and property of walk assessed (volume versus length), we obtain a four-fold polychotomization with one cell empty which mirrors Freeman's 1979 categorization. At a more substantive level, measures of centrality summarize a node's involvement in or contribution to the cohesiveness of the network. Radial measures in particular are reductions of pair-wise proximities cohesion to attributes of nodes or actors. The usefulness and interpretability of radial measures depend on the fit of the cohesion matrix to the one-dimensional model. In network terms, a network that is fit by a one-dimensional model has a core-periphery structure in which all nodes revolve more or less closely around a single core. This in turn implies that the network does not contain distinct cohesive subgroups. Thus, centrality is shown to be intimately connected with the cohesive subgroup structure of a network.