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Analyzing the Maritime Transportation System in Greece: a Complex Network Approach

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Abstract

Maritime networks of coastal and insular countries constitute fundamental transportation systems affecting the economy and the developmental dynamics of their countries. Under this perspective, the present article studies the Greek Maritime transportation Network (GMN), by using a complex network approach for the part of structural analysis and empirical techniques for the socioeconomic evaluation of the GMN’s topology. A methodological framework is developed for dealing with the GMN’s disconnectivity, which is evaluated by the empirical analysis. The curve fitting procedure on the degree distribution data indicated the existence of some scale-free network properties of the GMN, which seemed to be also captured as high correlations between pairs of binary and their homologous distance-weighted node structural variables, electing a topic of further empirical research on various networks. This status implies a kind of GMN’s structural indifference to distance, favoring the development of transportation activities into greater distances within the GMN. Also, the linear regression analysis modeled the connectivity of the GMN, electing topological, spatial and socioeconomic information. Finally, this paper elected the utility of complex network analysis in the study of national maritime networks, capable in providing new insights to the transportation policy makers of Greece.

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References

  • Albert R, Barabasi A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys 74(1):47–97

    Article  Google Scholar 

  • Barabasi A-L, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512

    Article  Google Scholar 

  • Barthelemy M (2011) Spatial networks. Phys Rep 499:1–101

    Article  Google Scholar 

  • Bastian M, Heymann S, Jacomy M (2009) Gephi: An open source software for exploring and manipulating networks, Proceedings of the Third International ICWSM Conference

  • Blumenfeld-Lieberthal E (2008) The topology of transportation networks. Netw Spat Econ 9:427–458

    Article  Google Scholar 

  • Borgatti S, Halgin D (2011) On network theory, Organization Science, Articles in Advance, pp.1-14, doi:10.1287/orsc.1110.0641

  • Brandes U (2001) A faster algorithm for betweenness centrality. J Math Sociol 25(2):163–177

    Article  Google Scholar 

  • Caschili S, Medda F, Parola F, Ferrari C (2014) An analysis of shipping agreements: the cooperative container network. Netw Spat Econ. doi:10.1007/s11067-014-9230-1

    Google Scholar 

  • Conover W (1980) Practical nonparametric statistics, 2nd edn. Wiley, New York

    Google Scholar 

  • Devore J, Berk K (2012) Modern mathematical statistics with applications. Springer-Verlag Publications, London

    Book  Google Scholar 

  • Diakomihalis M (2007) Greek maritime tourism: evolution, structures and prospects. Res Transp Econ 21:419–455

    Article  Google Scholar 

  • Diestel R (2005) Graph theory, 3rd edn. Springer-Verlag Publications, Heidelberg

    Google Scholar 

  • Ducruet C, Beauguitte L (2013) Spatial science and network science: review and outcomes of a complex relationship. Netw Spat Econ. doi:10.1007/s11067-013-9222-6

    Google Scholar 

  • Ducruet C, Notteboom T (2012) The worldwide maritime network of container shipping: spatial structure and regional dynamics. Global Networks 12(3):342–395

    Article  Google Scholar 

  • Ducruet C, Rozenblat C, Zaidi F (2010) Ports in multi-level maritime networks: evidence from the Atlantic (1996–2006). J Transp Geogr 18:508–518

    Article  Google Scholar 

  • Easley D, Kleinberg J (2010) Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press, Oxford

    Book  Google Scholar 

  • Epilogi (2006) The prefectures of Greece. All Media Publications, Athens

    Google Scholar 

  • Erdos P, Renyi A (1959) On random graphs I. Publ Math Debr 6:290–297

    Google Scholar 

  • Fremont A (2007) Global maritime networks: The case of Maersk. J Transp Geogr 15:431–442

    Article  Google Scholar 

  • Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning. Data mining, inference and prediction, 2nd edn. Springer-Verlag Publications, New York

    Google Scholar 

  • Hellenic Statistical Service (ELSTAT) (2011) Results of the Census of Population-Habitat 2011 referring to the permanent population of Greece, Newspaper of Government (ΦΕΚ), Second Issue (Τ-Β), Number 3465, 28-12-12

  • Hellenic Statistical Service (ESYE) (2008) Commodity and passengers Data per Greek port, available at www.statistics.gr/portal/page/portal/ESYE/PAGE-database, database last updated 03/12/2008

  • Hu Y, Zhu D (2009) Empirical analysis of the worldwide maritime transportation network. Physica A 388:2061–2071

    Article  Google Scholar 

  • Koschutzki D, Lehmann K, Peeters L, Richter S (2005) Centrality indices. In: Brandes U, Erlebach T (eds) Network analysis. Springer-Verlag Publications, Berlin, pp 16–61

    Chapter  Google Scholar 

  • Latapy M (2008) Main-memory triangle computations for very large (sparse (power-law)) graphs. Theor Comput Sci 407:458–473

    Article  Google Scholar 

  • Lin J (2012) Network analysis of China’s aviation system, statistical and spatial structure. J Transp Geogr 22:109–117

    Article  Google Scholar 

  • Marquez-Ramos L, Martinez-Zarzoso I, Perez-Garcia E, Wilmsmeier G (2011) Special Issue on Latin-American Research Maritime Networks, Services Structure and Maritime Trade. Netw Spat Econ 11:555–576

    Article  Google Scholar 

  • Massey F (1951) The Kolmogorov-Smirnov test for goodness of fit. J Am Statist Assoc 46:68–78

    Article  Google Scholar 

  • Newman M (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74:036104

    Article  Google Scholar 

  • Norusis M (2004) SPSS 13, Advanced statistical procedures companion. Prentice Hall Publications, New Jersey

    Google Scholar 

  • Norusis M (2005) SPSS 14.0 Statistical Procedures Companion. Prentice Hall Publications, New Jersey

    Google Scholar 

  • Notteboom T (2004) Container shipping and ports: an overview. Rev Netw Econ 3(2):86–106

    Article  Google Scholar 

  • O’Kelly M (2014) Network hub structure and resilience. Netw Spat Econ. doi:10.1007/s11067-014-9267-1

    Google Scholar 

  • Onnela JP, Saramaki J, Kertesz J, Kaski K (2005) Intensity and coherence of motifs in weighted complex networks, Physical Review E 71, 065103(R)

  • Polyzos S, Tsiotas D, Kantlis A (2013a) Determining the tourism developmental dynamics of the Greek regions, by using TALC Theory. TOURISMOS Int Multidisciplinary J Tourism 8(2):159–178

    Google Scholar 

  • Polyzos S, Tsiotas D, Sdrolias L (2013b) Greek regional productivity at the period of the economic crisis: obtaining information by using Shift–Share analysis. MIBES Transact 7:92–109

    Google Scholar 

  • Polyzos S, Tsiotas D, Niavis S (2014) Analyzing the location decisions of agro-industrial investments in Greece. Int J Agri Environ Info Syst, forthcoming

  • Schintler et al (2007) Using raster-based gis and graph theory to analyze complex networks. Netw Spat Econ 7:301–313

    Article  Google Scholar 

  • Sen P, Dasgupta S, Chatterjee A, Sreeram PA, Mukherjee G, Manna SS (2003) Small-world properties of the Indian railway network”. Phys Rev E 67:036106

    Article  Google Scholar 

  • Smirnov N (1948) Table for estimating the goodness of fit of empirical distributions”. Ann Math Stat 19:279–281

    Article  Google Scholar 

  • Szeto WY, Jiang Y, Wang DZW, Sumalee A (2013) A sustainable road network design problem with land use transportation interaction over time. Netw Spat Econ. doi:10.1007/s11067-013-9191-9

    Google Scholar 

  • Tang LC, Low JMW, Lam SW (2011) Understanding port choice behavior-A network perspective. Netw Spat Econ 11:65–82

    Article  Google Scholar 

  • Tsiotas D, Polyzos S (2013a) Introducing a new centrality measure from the transportation network analysis in. Ann Oper Res. doi:10.1007/s10479-013-1434-0

    Google Scholar 

  • Tsiotas D, Polyzos S (2013b) Interregional commuting under the Network Theoretical perspective: an empirical analysis from Greece. Proceedings of the Multidisciplinary Academic Conference on Transport, Logistics and Information Technology, Prague, Czech Republic, 9–10 May 2013 (ISBN 978-80-905442-0-8)

  • Tsiotas D, Polyzos S, Alexiou A (2012) Analyzing the interregional transportation network in Greece by using Graph Theory. Proceedings of the 3rd Pan-Hellenic Conference in Urban and Regional Planning and Development (Volos, Greece, 27–30 Sep 2012), 1100–1106 (Graphima Publications, ISBN: 978-960-6865-52-7)

  • Tzannatos E (2005) Technical reliability of the Greek coastal passenger fleet. Mar Policy 29:85–92

    Article  Google Scholar 

  • Wang J, Moa H, Wang F, Jin F (2011) Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach. J Transp Geogr 19:712–721

    Article  Google Scholar 

  • Watts D, Strogatz S (1998) Collective dynamics of small-world networks. Nature 393:440–442

    Article  Google Scholar 

  • Windeck V (2013) A linear shipping network design, routing and scheduling considering environmental influences. Springer Fachmedien Wiesbaden, Hamburg

    Book  Google Scholar 

  • Xie F, Levinson D (2009) Modeling the growth of transportation networks: A comprehensive review. Netw Spat Econ 9:291–307

    Article  Google Scholar 

  • Zwier R, Hiemstra F, Nijkamp P, van Montfort K (1955) Connectivity and Isolation in Transport Networks: A Policy Scenario Experiment for the Greek island Economy”. In: Coccossis H, Nijkamp P (eds) (1995) Overcoming Isolation, Information and Transportation Networks in Development Strategies for Peripheral Areas. Springer-Verlag Publications, Heidelberg, pp 205–234

    Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38 334, Greece

    Dimitrios Tsiotas & Serafeim Polyzos

Authors
  1. Dimitrios Tsiotas
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  2. Serafeim Polyzos
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Correspondence to Dimitrios Tsiotas.

Appendix

Appendix

Table 7 Results of correlation analysis (variables calculated on unweighted global sets - UGS)
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Table 8 Results of correlation analysis (variables calculated on weighted global sets - WGS)
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Tsiotas, D., Polyzos, S. Analyzing the Maritime Transportation System in Greece: a Complex Network Approach. Netw Spat Econ 15, 981–1010 (2015). https://doi.org/10.1007/s11067-014-9278-y

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