Pathways of change : shifting connectivities in the world city network, 2000-08

This is an empirical paper that measures and interprets changes in intercity relations at the global scale in the period 2000-08. It draws on the network model devised by the Globalization and World Cities (GaWC) research group to measure global connectivities for 132 cities across the world in 2000 and 2008. The measurements for both years are adjusted so that a coherent set of services/cities is used. A range of statistical techniques is used to explore these changes at the city level and the regional scale. The most notable changes are: the general rise of connectivity in the world city network; the loss of global connectivity of US and sub-Saharan African cities (Los Angeles, San Francisco and Miami in particular); and, the gain in global connectivity of south Asian, Chinese and eastern European cities (Shanghai, Beijing and Moscow in particular)

World City Network Expansion 2000-2004. An appraisal of the determinants of connectivity growth among world cities

The term “globalization” has long been vented indiscriminately everywhere with few being capable to either define or measure it. Cities are said to be at the forefront of the “works of globalization” by becoming coordinating centers for the transnational activities of multinational corporations. Ultimately, they become tied up to each other, as those activities require information inputs from different regions of the world. The article uses the advanced corporate service firms’ location patterns to measure the linkages between cities. As social, economical, cultural and political information about the cities flow through the firms’ network of branch offices, a highly connected city provides better corporate servicing to businessman wanting to do business elsewhere. By calculating the total connectivity of each city to the rest of the world, as well as total presence of global service firms within these cities, in the years 2000 and 2004, we produce a measure of the connectivity growth in the period. In a second moment, we use a linear regression model to test hypothesis concerning the determinants of connectivity growth in those cities. Results show us that connectivity growth in a city, in case of firm’s network expansion, display a “rich-get-rich” behavior on which well connected cities became even more connected. Furthermore, connectivity growth is responsive to competition, agglomeration economies, infrastructure, trade openness, human capital and the overall economic level of the country. Some of the variables behave differently according to the service firms’ sector being analyzed. In particular, we scrutinize the role of human capital as a determinant of connectivity growth in the management and banking sector, and interpret the results as a function of whether the sector is skilled-labor intensive (management) or capital intensive (banking).Globalization, World City Network, Interlock Network Model, Global City Model, Economic Geography, GaWC

Topological Measure Locating the Effective Crossover between Segregation and Integration in a Modular Network

We introduce an easily computable topological measure which locates the effective crossover between segregation and integration in a modular network. Segregation corresponds to the degree of network modularity, while integration is expressed in terms of the algebraic connectivity of an associated hyper-graph. The rigorous treatment of the simplified case of cliques of equal size that are gradually rewired until they become completely merged, allows us to show that this topological crossover can be made to coincide with a dynamical crossover from cluster to global synchronization of a system of coupled phase oscillators. The dynamical crossover is signaled by a peak in the product of the measures of intra-cluster and global synchronization, which we propose as a dynamical measure of complexity. This quantity is much easier to compute than the entropy (of the average frequencies of the oscillators), and displays a behavior which closely mimics that of the dynamical complexity index based on the latter. The proposed toplogical measure simultaneously provides information on the dynamical behavior, sheds light on the interplay between modularity vs total integration and shows how this affects the capability of the network to perform both local and distributed dynamical tasks

Logistics global network connectivity and its determinants. A European City network analysis

The Globalization and World City Research Network classifies global cities according to their connectivity through advanced producer service activities. Recent studies have suggested there is scope to develop a new classification of cities based on advanced logistics services. Within this framework, the aim of this paper is twofold: (i) to develop an interlocking Logistics Global Network for advanced logistics in Europe and measure the Logistics Global Network Connectivity (LGNC) of the host cities; (ii) to explore the variables explaining each the cities' score on the LGNC. The aim is achieved by means of a mixed methodological approach based on Taylor's Interlocking Network Model and via econometric analysis through Ordinary Least Square regression (OLS)

Studying Organisational Topology with Simple Computational Models

The behaviour of many complex systems is influenced by the underlying network topology. In particular, this applies to social systems in which people or organisational units collaboratively solve problems. Network rewiring processes are one useful tool in understanding the relationship between network topology and behaviour. Here we use the Kawachi network rewiring process, together with three simple simulation models of organisational collaboration, to investigate the network characteristics that influence performance. The simulation models are based on the Assignment Problem, the Kuramoto Model from physics, and a novel model of collaborative problem-solving which involves finding numbers with certain characteristics, the existence of which is guaranteed by Lagrange\'s Theorem. For all three models, performance is best when the underlying organisational network has a low average distance between nodes. In addition, the third model identified long-range connectivity between nodes as an important predictor of performance. The commonly-used clustering coefficient, which is a measure of short-range connectivity, did not affect performance. We would expect that long-range network connectivity would also influence the behaviour of other complex systems displaying global self-synchronization. The paper also demonstrates the utility of simple computational models in studying issues of organisational topology.Network Rewiring, Small World Networks, Self-Synchronization, Agent Simulation, Collaboration, Problem Solving

Identifying the underlying structure and dynamic interactions in a voting network

We analyse the structure and behaviour of a specific voting network using a dynamic structure-based methodology which draws on Q-Analysis and social network theory. Our empirical focus is on the Eurovision Song Contest over a period of 20 years. For a multicultural contest of this kind, one of the key questions is how the quality of a song is judged and how voting groups emerge. We investigate structures that may identify the winner based purely on the topology of the network. This provides a basic framework to identify what the characteristics associated with becoming a winner are, and may help to establish a homogenous criterion for subjective measures such as quality. Further, we measure the importance of voting cliques, and present a dynamic model based on a changing multidimensional measure of connectivity in order to reveal the formation of emerging community structure within the contest. Finally, we study the dynamic behaviour exhibited by the network in order to understand the clustering of voting preferences and the relationship between local and global properties.Comment: 20 pages, 10 figures, 3 tables, submitted to Physica