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Researching commuting to work using the methods of complex network analysis

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  • Pálóczi, Gábor

Abstract

In the current paper the possible utilization of complex network analysis in spatial researches was investigated. The organizational and developmental regularities of networks were demonstrated from the aspect of regional development planning. The reviewed regularities provide a new approach of the regional developments. The dependencies of settlements were analysed with the application of disparity method on the basis of the commuting matrix of the census from 2011. The disparity of out-commuting exceeded the level of in-commuting in all population categories, producing a more significant dependency relation in case of out-commuting. In general, the value of disparity increases with decreasing population number in settlements and dependency grows. This can be related with decrease in the level of degree and commuting distance. According to detailed results, the method of disparity might be effectively used in additional spatial analyses as well. The community detection procedures of the complex network analysis were also applied for spatial division. Modularity optimization with the Louvain method was successfully used in the delimitation of larger territorial units. Smaller units can be created by the increase of the resolution but modularity stability deteriorates. At the same time the composition of the units changes. In the light of the results, it could be stated that regions formed by commuting relations (according to the process of regionalism) did not match the Hungarian NUTS2 statistical regions, but natural borders and NUTS-3 level administrative boundaries could be detected in more cases. The differences between the results and NUTS-3 boundaries are not unique distortions caused by the methodology but these reflect real commuting relations (the local labour system units were discussed in a previous study). The methodology might be appropriate to detect the hierarchical order of the local labour system’s units. The method is adaptable for additional analysis of spatial interactions.

Suggested Citation

  • Pálóczi, Gábor, 2016. "Researching commuting to work using the methods of complex network analysis," MPRA Paper 74496, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:74496
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    References listed on IDEAS

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    1. Giovanni Russo & Aura Reggiani & Peter Nijkamp, 2007. "Spatial activity and labour market patterns: A connectivity analysis of commuting flows in Germany," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(4), pages 789-811, December.
    2. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, February.
    3. Kertesi, Gábor & Köllő, János, 1998. "Regionális munkanélküliség és bérek az átmenet éveiben. A bérszerkezet átalakulása Magyarországon II. rész [Regional unemployment and wages in the years of transition. Changes in the wage structure," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 621-652.
    4. Roberto Patuelli & Aura Reggiani & Sean Gorman & Peter Nijkamp & Franz-Josef Bade, 2007. "Network Analysis of Commuting Flows: A Comparative Static Approach to German Data," Networks and Spatial Economics, Springer, vol. 7(4), pages 315-331, December.
    5. Barthélemy, Marc & Barrat, Alain & Pastor-Satorras, Romualdo & Vespignani, Alessandro, 2005. "Characterization and modeling of weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(1), pages 34-43.
    6. De Montis, Andrea & Chessa, Alessandro & Campagna, Michele & Caschili, Simone & Deplano, Giancarlo, 2010. "Modeling commuting systems through a complex network analysis: A study of the Italian islands of Sardinia and Sicily," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 39-55.
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    More about this item

    Keywords

    network analysis; commuting; disparity; dependency; regionalization; community detection;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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