Trade in oil has undergone significant changes in the last 20 years: technical progress has allowed the exploitation of new and previously untapped fields; the emergence of new large oil importers, such as China, has shifted the traditional patterns of demand and supply, while the desire to diversify energy sources has favored the emergence of new suppliers. This paper compares the topological properties of the network of crude oil trade over the period 1995–2014. The analysis covers both aggregate measures (such as network density and centralization) and node-specific indicators (e.g. centrality) that allow to uncover the rise (demise) of new (old) important players. Accounting for the position of each country within the network provides valuable information above and beyond traditional measures such as market shares. To investigate whether oil trade has experienced a process of globalization or, rather, regionalization, we look at the community structure of the network: the number of communities increases in the aftermath of the global financial crisis, but then goes back to its historical values. Something similar happens to the average geographic distance within each community, showing that along a regional component there are also strategic/political considerations at play. Econometric analysis suggests that high oil prices increase the likelihood that high-production-cost exporters play a more central role in the network, thus reducing the power of traditional suppliers.

This study uses simulation over real and artificial networks to compare the eventual adoption outcomes of network interventions, operationalized as idealized contagion processes with different sets of seeds. While the performance depends on the details of both the network and behaviour adoption mechanisms, interventions with seeds that are central to the network are more effective than random selection in the majority of simulations, with faster or more complete adoption throughout the network. These results provide additional theoretical justification for utilizing relevant network information in the design of public health behavior interventions.

This paper explores the structural changes in the international organization of automotive production since the early 1990s. We apply descriptive network measures to international trade data for the period 1993–2013 for three automotive component groups with different technological intensity, with the aim of understanding (1) how the automotive international trade network has changed since the beginning of the 1990s; (2) whether regionalization has increased over time; (3) how the role that rising powers play within and between regions interacts with regionalization patterns. Our findings suggest that the structure of trade has changed significantly over the last two decades in all components. The network for electric and electrical parts and engines has evolved to become more hierarchical, with a cohesive core tied to hangers-on in the periphery, while the opposite has happened for rubber and metal. Regionalization patterns also show important differences across components. Finally, we have found an apparent association between the strengthening of regionalization patterns and the role played by traditional players and rising powers.

International trade has been increasingly organized in the form of global value chains (GVCs). In this paper, we provide a new method for comparing GVCs across countries and over time. First, we use the World Input–Output Database (WIOD) to construct both the upstream and the downstream global value networks. Second, we introduce a network-based measure of node similarity to compare the GVCs between any pair of countries for each sector and each year available in the WIOD. Our network-based similarity is a better measure for node comparison than the existing ones because it takes into account all the direct and indirect relationships between the country–sector pairs, is applicable to both directed and weighted networks with self-loops, and takes into account externally defined node attributes. As a result, our measure of similarity reveals the most intensive interactions among the GVCs across countries and over time. From 1995 to 2011, the average similarity between sectors and countries have clear increasing trends, which are temporarily interrupted by the recent economic crisis. This measure of the similarity of GVCs provides quantitative answers to important questions about dependency, sustainability, risk, and competition in the global production system.

In the original publication of this article (Abbate et al. 2018), a disclaimer was omitted. The authors wish to state the following:

The views expressed in this study are the authors' and do not necessarily reflect those of the Swiss National Bank.

The authors regret the omission.