César Ducruet

Bio: César Ducruet is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Port (computer networking) & Global shipping network. The author has an hindex of 34, co-authored 189 publications receiving 4127 citations. Previous affiliations of César Ducruet include Erasmus University Rotterdam & Paris-Sorbonne University.

The worldwide maritime network of container shipping: Spatial structure and regional dynamics

Abstract: Port and maritime studies dealing with containerization have observed traffic concentration and dispersion throughout the world. Globalization, intermodal transportation, and technological revolutions in the shipping industry have resulted in both network extension and rationalization. However, lack of precise data on inter-port relations prevent the application of wide network theories to global maritime container networks, which are often examined through case studies of specific firms or regions. This paper presents an analysis of the global liner shipping network in 1996 and 2006, a period of rapid change in port hierarchies and liner service configurations. While it refers to literature on port system development, shipping networks, and port selection, it is one of the only analyses of the properties of the global container shipping network. The paper analyzes the relative position of ports in the global network through indicators of centrality. The results reveal a certain level of robustness in the global shipping network. While transhipment hub flows and gateway flows might slightly shift among nodes in the network, the network properties remain rather stable in terms of the main nodes polarizing the network and the overall structure of the system. Additionally, mapping the changing centrality of ports confirms the impacts of global trade and logistics shifts on the port hierarchy and indicates that changes are predominantly geographic

Inter-similarity between coupled networks

Abstract: Recent studies have shown that a system composed of several randomly interdependent networks is extremely vulnerable to random failure. However, real interdependent networks are usually not randomly interdependent, rather pairs of dependent nodes are coupled according to some regularity which we coin inter-similarity. For example, we study a system composed of an interdependent world wide port network and a world wide airport network and show that well-connected ports tend to couple with well-connected airports. We introduce two quantities for measuring the level of inter-similarity between networks: i) the inter degree-degree correlation (IDDC); ii) the inter-clustering coefficient (ICC). We then show both by simulation models and by analyzing the port-airport system that as the networks become more inter-similar the system becomes significantly more robust to random failure.

Inter-similarity between coupled networks

Abstract: Recent studies have shown that a system composed from several randomly interdependent networks is extremely vulnerable to random failure. However, real interdependent networks are usually not randomly interdependent, rather a pair of dependent nodes are coupled according to some regularity which we coin inter-similarity. For example, we study a system composed from an interdependent world wide port network and a world wide airport network and show that well connected ports tend to couple with well connected airports. We introduce two quantities for measuring the level of inter-similarity between networks (i) Inter degree-degree correlation (IDDC) (ii) Inter-clustering coefficient (ICC). We then show both by simulation models and by analyzing the port-airport system that as the networks become more inter-similar the system becomes significantly more robust to random failure.

Centrality and vulnerability in liner shipping networks: revisiting the Northeast Asian port hierarchy

Abstract: This article is essentially an empirical investigation in the network analysis of inter-port traffic flows. Based on a database of vessel movements, it applies conventional techniques of network analysis to the graph of Northeast Asian liner networks in 1996 and 2006. Such an approach proves particularly helpful for analyzing the changing position of major hub ports and for revealing their respective tributary areas within the region. Despite rapid traffic growth at Chinese ports during the period under study, the latter seem to remain polarized by established hubs such as Korean ports and Hong Kong. This research reveals the strong relation between local port policies and the evolution of shipping network design.

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Multilayer Networks

Abstract: In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications Such systems include multiple subsystems and layers of connectivity, and it is important to take such "multilayer" features into account to try to improve our understanding of complex systems Consequently, it is necessary to generalize "traditional" network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other, and provide a thorough discussion that compares, contrasts, and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks, and many others We also survey and discuss existing data sets that can be represented as multilayer networks We review attempts to generalize single-layer-network diagnostics to multilayer networks We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions, and various types of dynamical processes on multilayer networks We conclude with a summary and an outlook

Applied Linear Regression Models

Abstract: (1991). Applied Linear Regression Models. Journal of Quality Technology: Vol. 23, No. 1, pp. 76-77.