Conference Agenda

The paper combines the methodology of Multiple Correspondence Analysis (MCA) and Social Network Analysis (SNA) to investigate the Brazilian business elite, focusing on the interlocking directorates and boards formed by 72 publicly traded companies whose shares were traded on B3 (Brazil's main stock exchange) in 2020. To this end, information about the executive boards and boards of directors of these companies was analyzed using R Studio software, with the reference forms annually submitted by the companies to the Securities and Exchange Commission (CVM) as the primary sources. Guided by a notion of elite based on Wright Mills' positional method and Pierre Bourdieu's construct of the field of power, the study aims to demonstrate how individuals' participation in organizations, their shared educational background, and their professional trajectories form a coordinated elite, which constitutes a necessary foundation for the exercise of power. We also mapped the relationship of these agents with national political and cultural spheres, investigating their participation as members of the government, cultural institutions (such as family and private foundations and think tanks), and social clubs. We used SNA to identify groupings or communities (community detection) through clustering algorithms (stochastic block modeling), enabling the creation of an active categorical variable to be included in the MCA. This methodological combination contributes to the sociology of elites by making it possible to objectify social capital and the multi-positionality of agents and to assess the influence of these elements on the structure of social space.

Firms exchange various valuable resources to accomplish their daily tasks and achieve their goals. However, the process of tie formation in networks of business transactions between firms is still unclear. We follow and combine previous knowledge from the sociology of organizations, network science, and economic geography to inspire our research hypotheses on how we can potentially describe and infer the substructures that may better represent their network formation processes. We define our networks with firms as nodes and economic transactions between them as edges, which we observe from the 2017 Hungarian VAT declaration records. We construct our networks from transactions between firms of the specific industry-region, their economic transactions with external partners from different industries and regions, and the transactions between these partners. We focus on firms operating in the metal production sector (N=10 networks). Using Bayesian ERGMs, our preliminary results show that structural and actor-relation effects are relevant and significant in identifying the process of tie formation in these networks. Firms in this sector in 2017 relied on existing connections for their exchanges, and typically did not engage in circular trade patterns. Moreover, there was limited preferential attachment in these networks, suggesting that firms imposed capacity and risk constraints. Our contribution extends to the possibility of applying these models to other industries, as well as identifying trends that may be useful for further studies that need to set prior distributions when using Bayesian estimation as a solution for sparse network inference.

Corporate interlocks—the sharing of directors across multiple company boards—create influential networks through which cybersecurity knowledge and practices flow between organisations. These connections are remarkably common: in 2018, 78% of the top 50 S&P500 firms shared at least one director. Despite recent trends limiting multiple directorships—59% of S&P500 firms cap directors at three additional positions—these interconnections remain powerful in corporate governance.

These directorate networks serve as channels through which cybersecurity attitudes propagate across organisational boundaries. Beyond individual application of experience, these networks facilitate collective learning as board members exchange insights. Interlocks function as effective external knowledge sources, providing access to insider strategies that would otherwise remain confined.

Our study employs a Linear Network Autocorrelation Model (LNAM) to examine how interlocks influence cybersecurity governance across S&P500 companies. We analyse key variables including Risk and Audit committee structures, presence of CROs and CISOs, board size, women directors, governance quality scores, and ransomware experiences, while controlling for industry effects. This approach reveals how cybersecurity practices diffuse through director networks and identifies which governance characteristics most effectively enhance cyber resilience.

This study examines the impact of ethnic social capital on wages in Singapore, focusing on the contrasting effects of Chinese and Malay social ties. Using data from Wave 2 of a 2023 study of approximately 900 young adults (aged 21-39) from lower to middle-income households, the analysis reveals that in a labour market where education, occupation, and experience are the primary determinants of wages, social capital plays a comparatively minor role. However, a notable asymmetry emerges: while Chinese social capital has minimal or no effect on wages, Malay social capital is linked to a significant wage penalty. Among degree holders and PMETs, having more Malay contacts correlates with lower wages, even when these contacts are high-status. To address the possibility of reverse causality—where the negative link between Malay social capital and wages could stem from more Malays occupying lower-wage jobs—the study controls for workplace ethnic composition. Additionally, by controlling for the respondent’s ethnicity, the analysis confirms that the wage penalty is driven by the devaluation of Malay social networks, not the respondent’s ethnicity. These findings highlight the devaluation of Malay social capital and point to underlying racial biases and structural inequalities in Singapore’s multi-ethnic labour market, even among highly qualified individuals.

In the current context of globalization, this research explores the networks of multinational firms in African cities. Historically, the colonial era structured African economic relations, remaining after the countries’ independences. For 10 years, African cities have diversified their globalization, supported by the emergence of new partnerships (Martin, 2023; Chaumont, 2024).

We undertook an empirical study of the ownership networks of multinational companies based on the ORBIS-BvD 2010–2022 dataset, a sample of the top 3,000 global groups’ networks of firms (all their direct and indirect subsidiaries with ownership above 10%) in 2010, 2013, 2016, 2019, and 2022). We located 98% of the African companies in homogenized Large Urban regions (LURs) (Rogromel & Rozenblat, 2024) building weighted and oriented inter and intra-city networks.

Between 2010 and 2022, the number of firms of the sample in African cities significantly increased from 2,400 to 28,000, with links rising from 3,700 to 28,000 (Orbis-BvD-Citadyne Unil, 2010–2022). This evolution reflects not only a growing integration in globalization but overall, the growth of intra-urban, intranational, and intracontinental urban networks, while the intercontinental networks lost their domination. The African Continental Free Trade Area (AfCFTA) agreements, by simplifying regulations and opening African markets, have significantly accelerated this intra-continental integration (Obida, 2019). Cities such as Port-Louis, Cairo, Lagos, and Johannesburg became regional hubs, concentrating these intra-African interurban networks. While a vertical structure dominates with political or economic capitals, a horizontal structure emerges where specialized cities interact in a complementary fashion with the major hubs.