The promise and perils of using big data in the study of corporate networks: problems, diagnostics and fixes

Heemskerk, Eelke M.; Young, Kevin; Takes, Frank W.; Cronin, Bruce; Garcia‐Bernardo, Javier; Henriksen, Lasse Folke; Winecoff, W. Kindred; Попов, В. А.; Laurin‐Lamothe, Audrey

doi:10.1111/glob.12183

Cited by 32 publications

(16 citation statements)

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“…Although we now have an understanding of the basic building blocks of the corporate network of Germany, in future work it could be interesting to perform a cross-country comparison, investigating if the prominent presence of particular sectors is as prevalent in other countries. The coming of age of large-scale corporate network analysis will certainly benefit from including motif analysis in the research agenda ( Heemskerk et al 2018 ). For example, a longitudinal analysis can reveal how the meso level building blocks of corporate networks in different countries change over time.…”

Section: Discussionmentioning

confidence: 99%

Multiplex network motifs as building blocks of corporate networks

et al. 2018

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In corporate networks, firms are connected through links of corporate ownership and shared directors, connecting the control over major economic actors in our economies in meaningful and consequential ways. Most research thus far focused on the connectedness of firms as a result of one particular link type, analyzing node-specific metrics or global network-based methods to gain insights in the modelled corporate system.In this paper, we aim to understand multiplex corporate networks with multiple types of connections, specifically investigating the network’s essential building blocks: multiplex network motifs. Motifs, which are small subgraph patterns occurring at significantly higher frequencies than in similar random networks, have demonstrated their usefulness in understanding the structure of many types of real-world networks. However, detecting motifs in multiplex networks is nontrivial for two reasons. First of all, there are no out-of-the-box subgraph enumeration algorithms for multiplex networks. Second, existing null models to test network motif significance, are unable to incorporate the interlayer dependencies in the multiplex network. We solve these two issues by introducing a layer encoding algorithm that incorporates the multiplex aspect in the subgraph enumeration phase. In addition, we propose a null model that is able to preserve the interlayer connectedness, while taking into account that one of the link types is actually the result of a projection of an underlying bipartite network.The experimental section considers the corporate network of Germany, in which tens of thousands of firms are connected through several hundred thousand links. We demonstrate how incorporating the multiplex aspect in motif detection is able to reveal new insights that could not be obtained by studying only one type of relationship. In a general sense, the motifs reflect known corporate governance practices related to the monitoring of investments and the concentration of ownership. A substantial fraction of the discovered motifs is typical for an industrialized country such as Germany, whereas others seem specific for certain economic sectors. Interestingly, we find that motifs involving financial firms are over-represented amongst the larger and more complex motifs. This demonstrates the prominent role of the financial sector in Germany’s largely industry-oriented corporate network.

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Section: Discussionmentioning

confidence: 99%

Multiplex network motifs as building blocks of corporate networks

et al. 2018

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“…Network data on corporate connections have been increasingly used to examine important questions pertaining to modern capitalism (Babic, Fichtner, and Heemskerk 2017;Heemskerk et al 2018). SNA is often used to empirically analyze WCNs based on intrafirm data on ownership structure and office locations.…”

Section: Methodsmentioning

confidence: 99%

Spatial Differentiation of Variegated Capitalisms: A Comparative Analysis of Russian and Australian Oil and Gas Corporate City Networks

et al. 2020

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“…We then searched for the ties of these individuals outside the organizations originally sampled. 7 We conducted a variety of quality control checks following the best practice standards (Heemskerk et al 2018). In particular, we conducted checks on entity resolution (Marple et al 2017) using sorted lists of organizations and names, and looking up organizations when names were ambiguous.…”

Section: Discussionmentioning

confidence: 99%

How white is the global elite? An analysis of race, gender and network structure

et al. 2020

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Research on elites often utilizes network analysis to describe and analyse the interrelationships among elites and how their prominence varies by demographic characteristics. We examine the diversity of global elites through an analysis of the board members of large corporations, think tanks, international organizations, and transnational policy planning groups. Using new data, we provide the first descriptive picture of global elite networks in terms of race and gender. We also test the ‘core–periphery’ hypothesis, which predicts that as non‐whites and women achieve elite positions they will be marginalized to the periphery of elite networks, while the core remains significantly more white and male. We find consistent evidence for the core–periphery hypothesis across a range of empirical tests, from simple k‐coring to various core–periphery models. Most groups decline in their representation in the core, and this includes white women. White men are the only group that increases in representation in the core compared to the periphery.

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The promise and perils of using big data in the study of corporate networks: problems, diagnostics and fixes

Abstract: Network data on connections between corporate actors and entities -for

Cited by 32 publications

References 71 publications

Multiplex network motifs as building blocks of corporate networks

Multiplex network motifs as building blocks of corporate networks

Spatial Differentiation of Variegated Capitalisms: A Comparative Analysis of Russian and Australian Oil and Gas Corporate City Networks

How white is the global elite? An analysis of race, gender and network structure

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