S.Caschili and F.R.Medda In Table 1 we highlight the similarities and differences between our two selected studies on the GCSN.Kaluza et al.[7]use the Lloyd's Register Fairplay for year 2007,while Ducruet and Notteboom [5]utilize the dataset from Lloyd's Marine Intelligence Unit for years 1996 (post-Panamax vessels period)and 2006(introduction of 10 000+TEU vessels). By applying different approaches to the network analysis,both studies reach different conclusions in some cases.Ducruet and Notteboom build two different network structures: the first(Graph of Direct Links-GDL)only takes into account the direct links generated by ships mooring at subsequent ports,and the second(Graph of All Linkages-GAL)includes the direct links between ports which are called at by at least one ship.Kaluza et al.[7] differentiate among movements according to type of ship and subsequently construct four networks:all available links,sub-network of container ship,bulk dry carriers,and oil tankers. Despite clear differences between the approaches adopted in the two studies,in order to compare them,we consider the complete network of ship movements from Kaluza et al.[7], and the GAL network of Ducruet and Notteboom [5]. All the networks are dense(average ratio between number of edges and nodes is 37,2).Some network measures indicate a tendency for the GCSN to belong to the class of small world networks2,given the high values of the Clustering Coefficient3.Small world networks are a special class of networks characterized by high connectivity between nodes(or in other words Table 1.Overview of the main features of the GCSN as proposed Kaluza et al.[7]and Ducruet and Notteboom [5]. Kaluza et al.network GAL (Year 1996) GAL (Year 2006) (Year2007)[Z] [ [ Asymmetric(59% connections in one Weighted indirect Weighted indirect Main features direction);structural network;small network:small robustness(densely network network connected) Total 11 226;Container Vessels ships 3100;Bulk dry carriers 5498;Oil Container ship 1759 Container ship 3973 tankers 2628 Weights Sum of cargo capacity between port i and port Not specified Not specified No.of nodes 951 910 1205 No.of links 36351 28510 51057 Min.shortest path 2,5 2.23 2,21 Clustering coeff. 0,49 0.74 0,73 Average degree; 76,5;- 64,1;437 87,5:610 Max.degree P(k) Right skewed but not -0.62 -0,65 power law P(w) Power law(1,71±0,14) Suez and Panama Strong correlation Betweenness Canals have high between degree and Centrality centrality with some centrality (vulnerability of the exceptions GCSN)S. Caschili and F.R. Medda 6 In Table 1 we highlight the similarities and differences between our two selected studies on the GCSN. Kaluza et al. [7] use the Lloyd’s Register Fairplay for year 2007, while Ducruet and Notteboom [5] utilize the dataset from Lloyd’s Marine Intelligence Unit for years 1996 (post-Panamax vessels period) and 2006 (introduction of 10 000+ TEU vessels). By applying different approaches to the network analysis, both studies reach different conclusions in some cases. Ducruet and Notteboom build two different network structures: the first (Graph of Direct Links – GDL) only takes into account the direct links generated by ships mooring at subsequent ports, and the second (Graph of All Linkages – GAL) includes the direct links between ports which are called at by at least one ship. Kaluza et al. [7] differentiate among movements according to type of ship and subsequently construct four networks: all available links, sub-network of container ship, bulk dry carriers, and oil tankers. Despite clear differences between the approaches adopted in the two studies, in order to compare them, we consider the complete network of ship movements from Kaluza et al. [7], and the GAL network of Ducruet and Notteboom [5]. All the networks are dense (average ratio between number of edges and nodes is 37,2). Some network measures indicate a tendency for the GCSN to belong to the class of small world networks2 , given the high values of the Clustering Coefficient3 . Small world networks are a special class of networks characterized by high connectivity between nodes (or in other words Table 1. Overview of the main features of the GCSN as proposed Kaluza et al. [7] and Ducruet and Notteboom [5]. Kaluza et al. network (Year 2007) [7] GAL (Year 1996) [5] GAL (Year 2006) [5] Main features Asymmetric (59% connections in one direction); structural robustness (densely connected) Weighted indirect network; small network Weighted indirect network; small network # Vessels Total 11 226; Container ships 3100; Bulk dry carriers 5498; Oil tankers 2628 Container ship 1759 Container ship 3973 Weights Sum of cargo capacity between port i and port j Not specified Not specified No. of nodes 951 910 1205 No. of links 36 351 28 510 51 057 Min. shortest path 2,5 2.23 2,21 Clustering coeff. 0,49 0.74 0,73 Average degree; Max. degree 76,5; - 64,1; 437 87,5; 610 P(k) Right skewed but not power law -0,62 -0,65 P(w) Power law (1,71 ± 0,14) - - Betweenness Centrality Strong correlation between degree and centrality with some exceptions Suez and Panama Canals have high centrality (vulnerability of the GCSN)