Congress of the European Regional Science Association 23-27 August 2005, Free University of Amsterdam Emergent topological and dynamical properties of a real inter-municipal commuting network: perspectives for policy-making and planning Andrea De Montis (1) , Marc Barthélémy (2) , Michele Campagna (3) , Alessandro Chessa (4) , Alessandro Vespignani (5) (1) Dipartimento di Ingegneria del Territorio, Sezione Costruzioni e Infrastrutture, Università degli Studi di Sassari Via De Nicola – 07100 Sassari, Italy, e-mail: andreadm@uniss.it (2) CEA-Centre d’Etudes de Bruyères-le-Châtel, Département de Physique Théorique et Appliquée BP12, 91680 Bruyères-le-Châtel, France, e-mail: Marc.Barthelemy@th.u-psud.fr (3) Dipartimento di Ingegneria del Territorio, Sezione Urbanistica, Università degli Studi di Cagliari, piazza d’Armi, 16, 09123 Cagliari, e- mail: campagna@unica.it (4) Dipartimento di Fisica, Università degli Studi di Cagliari, Cittadella Universitaria di Monserrato, 09042 Monserrato, Italy, e-mail: alessandro.chessa@dsf.unica.it (5) School of Informatics, Center for Biocomplexity and Department of Physics, Indiana University, Bloomington, USA, e-mail: alexv@indiana.edu Abstract In the domains of urban and environmental planning, spatial analysis and regional science, many scholars have showed in the past years an increasing interest for the research developments on complex networks. Their positions range from the theory statements on the need to apply complex network analysis to spatial phenomena (Salingaros, 2001) to the empirical focus on more quantitative research about urban space syntax (Jiang and Claramunt, 2004). As regards transportation systems analysis, interesting results have been obtained in the study of networked subway (Latora and Marchiori, 2002; Gastner and Newman, 2004) and airports (Barrat et al, 2004) systems. In this paper, the authors aim at the study of the inter-municipal commuting network of Sardinia, Italy, described by the system of study or work-led habitual movements of its citizens. In this complex network, the nodes correspond to urban centres while the links to positive commuting exchanges among municipal towns. Following the analysis developed by Barrat et al. (2004), topological and dynamical properties are investigated as they stem from the underlying complex network. Furthermore, in the perspective of policy-making and planning, the emerging network behaviours are critically compared to the geographical, social and demographical aspects of the transportation system. JEL classification codes: R15, R40, Z13 Key-words: small worlds, scale free networks, weighted complex networks, commuting networks, socio-economic networks