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Comparison of Two Network-Theory-Based Methods for detecting Functional Regions

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1. Ball, R. M. (1980) ”The use and definition of travel-to-work areas in Great Britain: some problems”, Regional Studies, Vol. 14, No. 2, pp. 125-139.10.1080/09595238000185121Search in Google Scholar

2. Benassi, F. Deva, M., Zindato, D. (2015), “Graph regionalization with clustering and partitioning: an application for daily commuting flows in Albania”, Regional Statistics, Vol. 5, No. 1, pp. 25-43.10.15196/RS05102Search in Google Scholar

3. Boss, M., Elsinger, H., Summer, M., Thurner, S. (2004), “Network topology of the interbank market”, Quantitative Finance, Vol. 4, No. 6, pp. 677-684.10.1080/14697680400020325Search in Google Scholar

4. Casado-Diaz, J. M. (2000), “Local labour market areas in Spain: a case study”, Regional Studies, Vol. 34, pp. 843-856.10.1080/00343400020002976Search in Google Scholar

5. Clauset, A., Moore, C., Newman, M. E. J. (2008), “Hierarchical structure and the prediction of missing links in networks”, Nature, Vol. 453, No. 7191, pp. 98-101.10.1038/nature06830Search in Google Scholar

6. Coombes, M. G., Green, A. E., Openshaw, S. (1986), “An efficient algorithm to generate official statistical reporting areas: the case of the 1984 travel-to-work-areas revision in Britain”, Journal of the Operational Research Society, Vol. 37, No. 10, pp. 943-953.10.1057/jors.1986.163Search in Google Scholar

7. Coombes, M., Bond, S. (2008), “Travel-to-Work Areas: the 2007 review Office for National Statistics”, London, available at: https://www.ncl.ac.uk/media/wwwnclacuk/curds/files/TTWA%20report.pdf (25 February 2016)Search in Google Scholar

8. Coombes, M., Casado-Díaz, J. M., Martínez-Bernabeu, L., Carausu, F. (2012), “Study on comparable labour market areas - Final research report”, available at: http://www.istat.it/it/files/2014/12/Final-Report_LMA-v1-0-17102012.pdf (25 March 2016).Search in Google Scholar

9. Cörvers, F., Hensen, M., Bongaerts, D. (2009), “Delimitation and coherence of functional and administrative regions”, Regional Studies, Vol. 43, No. 1, pp. 19-31.10.1080/00343400701654103Search in Google Scholar

10. Csardi, G., Nepusz, T., (2006), “The igraph software package for complex network research”, InterJournal Complex Systems, Vol. 1695, No. 5, pp. 1-9.Search in Google Scholar

11. Drobne, A., Lakner, M. (2016), “Use of constraints in the hierarchical aggregation procedure Intramax”, Business Systems Research, Vol. 7, No. 2, pp. 5-22.10.1515/bsrj-2016-0009Search in Google Scholar

12. Drobne, S. (2016), “Model vrednotenja števila in območij funkcionalnih regij” (A model evaluating the number and areas of functional regions), PhD thesis, University of Ljubljana, available at: https://repozitorij.uni-lj.si/Dokument.php?id=97829&lang=slv (7 November 2019).Search in Google Scholar

13. Drobne, S., Bogataj, M. (2014), “Regions for servicing old people: case study of Slovenia”, Business Systems Research, Vol. 5 No. 3, pp. 19-36.10.2478/bsrj-2014-0017Search in Google Scholar

14. Drobne, S., Garre, A., Hontoria, E., Konjar, M. (2019), “Functional regions detection by Walktrap and chains′ methods”, in Zadnik Stirn, L., Kljajić Borštnar, M. Žerovnik, J., Drobne, S., Povh, J. (Eds.), 15th International Symposium on Operational Research, 25-27 September, Slovenian Society Informatika, Bled, pp. 449-454.Search in Google Scholar

15. Drobne, S., Konjar, M., Lisec, A. (2010), “Razmejitev funkcionalnih regij Slovenije na podlagi analize trga dela” (Delimitation of functional regions of Slovenia based on labour market analysis), Geodetski vestnik, Vol. 54, No. 3, pp. 481-500.10.15292/geodetski-vestnik.2010.03.481-500Search in Google Scholar

16. Erlebach, M., Tomáš, M., Tonev, P. (2016), “A functional interaction approach to the definition of meso regions: the case of the Czech Republic”, Moravian Geographical Reports, Vol. 24, No. 2, pp. 37-46.10.1515/mgr-2016-0009Search in Google Scholar

17. Faloutsos, M., Faloutsos, P., Faloutsos, C. (1999), “On power-law relationships of the internet topology”, ACM SIGCOMM Computer Communication Review, Vol. 29, No. 4, 251-262.10.1145/316194.316229Search in Google Scholar

18. Feng, Z. (2009), “Fuzziness of travel to work areas”, Regional Studies, Vol. 43, No. 5, pp. 707-720.10.1080/00343400801922806Search in Google Scholar

19. Fortunato, S. (2010), “Community detection in graphs”, Physics Reports, Vol. 486, No. 3-5, pp. 75-174.10.1016/j.physrep.2009.11.002Search in Google Scholar

20. Gabrovec, M., Bole, D. (2009), “Dnevna mobilnost v Sloveniji” (Daily mobility in Slovenia), available at: https://giam.zrc-sazu.si/sites/default/files/9789612541187.pdf (25 February 2020).10.3986/9789612545550Search in Google Scholar

21. Garre, A., Frenandez, P.S., Brereton, P., Elliott, C., Mojtahed, V. (2019), “The use of trade data to predict the source and spread of food safety outbreaks: An innovative mathematical modelling approach”, Food Research International, Vol. 123, pp. 717-721.10.1016/j.foodres.2019.06.007Search in Google Scholar

22. GURS. (2018), “Spatial data on municipalities, 2011”, available at: https://egp.gu.gov.si/egp/ (15 August 2018).Search in Google Scholar

23. Halás, M., Klapka, P., Erlebach, M. (2019), “Unveiling spatial uncertainty: a method to evaluate the fuzzy nature of functional regions”, Regional Studies, Vol. 53, No. 7, pp 1029-1041.10.1080/00343404.2018.1537483Search in Google Scholar

24. Halás, M., Klapka, P., Hurbánek, P., Bleha, B., Pénzes, J., Pálóczi, G. (2018), “A definition of relevant functional regions for international comparisons: The case of Central Europe”, Area, Vol. 51, pp. 489-499.10.1111/area.12487Search in Google Scholar

25. Halás, M., Klapka, P., Tonev, P., Bednář, M. (2015), “An alternative definition and use for the constraint function for rule-based methods of functional regionalisation”, Environment and Planning A, Vol. 47, pp. 1175-1191.10.1177/0308518X15592306Search in Google Scholar

26. Holmes, J. H., Haggett, P. (1977), “Graph theory interpretation of flow matrices: a note on maximization procedures for identifying significant links”, Geographical Analysis, Vol. 9, pp. 388-399.10.1111/j.1538-4632.1977.tb00591.xSearch in Google Scholar

27. Karlsson, C., Olsson, M. (2006), “The identification of functional regions: theory, methods, and applications”, The Annals of Regional Science, Vol. 40, No. 1, pp. 1-18.10.1007/s00168-005-0019-5Search in Google Scholar

28. Ke, W., Chen, W., Yu, Z. (2017), “Uncovering spatial structures of regional city networks from expressway traffic flow data: A case study from Jiangsu province, China”, Sustainability, Vol. 9, No. 9, pp. 1541.10.3390/su9091541Search in Google Scholar

29. Khatoon, M., Banu, W. A. (2019), “An efficient method to detect communities in social networks using DBSCAN algorithm”, Social Network Analysis and Mining, Vol. 9, No. 1, 9.10.1007/s13278-019-0554-1Search in Google Scholar

30. Konjar, M., Lisec, A., Drobne, S. (2010), “Methods for delineation of functional regions using data on commuters”, in Painho, M., Santos, M. Y., Pundt, H. (Eds.), 13th AGILE International Conference on Geographic Information Science, May 10-14, Guimarães, Springer-Verlag, pp. 1-10.Search in Google Scholar

31. Laan van der, L., Schalke, R. (2001), “Reality versus policy: the delineation and testing of local labour market and spatial policy areas”, European Planning Studies, Vol. 9, No. 2, pp. 201-221.10.1080/09654310123131Search in Google Scholar

32. Lehmann, S., Schwartz, M., Hansen, L.K., (2008), “Biclique communities”, Physical Review E, Vol. 9, No. 1, 016108.10.1103/PhysRevE.78.016108Search in Google Scholar

33. Masser, I., Brown, P. J. B. (1975), “Hierarchical aggregation procedures for interaction data”, Environment and Planning A, Vol. 7, No. 5, pp. 509-523.10.1068/a070509Search in Google Scholar

34. Masser, I., Scheurwater, J. (1978), “The specification of multi-level systems for spatial analysis”, in: Masser, I., Brown, P. J. B. (Eds.), Spatial representation and spatial interaction, Springer US, Leiden and Boston, pp. 151-172.10.1007/978-1-4613-4067-6_7Search in Google Scholar

35. Masser, I., Scheurwater, J. (1980), “Functional regionalisation of spatial interaction data: an evaluation of some suggested strategies”, Environment and Planning A, Vol. 12, No. 12, pp. 1357-1382.10.1068/a121357Search in Google Scholar

36. Newman, M. (2010), Networks: An introduction, Oxford University Press, New York.Search in Google Scholar

37. Nystuen, J. D., Dacey, M. F. (1961), “A graph theory interpretation of nodal regions”, Papers of the Regional Science Association, Vol. 7, pp. 29-42.10.1007/BF01969070Search in Google Scholar

38. Pálóczi, G., Pénzes, J., Hurbánek, P., Halás, M., Klapka, P. (2016), “Attempts to delineate functional regions in Hungary based on commuting data”, Regional Statistics, Vol. 6, No. 1, pp. 23-41.10.15196/RS06102Search in Google Scholar

39. Pons, P., Latapy, M. (2006), “Computing communities in large networks using random walks”, Journal of Graph Algorithms and Applications, Vol. 10, No. 2, pp. 191-218.10.7155/jgaa.00124Search in Google Scholar

40. R Core Team. (2016), “R: a language and environment for statistical computing”, available at: https://www.R-project.org/ (7 November 2019).Search in Google Scholar

41. Ronhovde, P., Nussinov, Z. (2009), “Multiresolution community detection for megascale networks by information-based replica correlations”, Physical Reviews E, Vol. 80, No. 1, 016109.10.1103/PhysRevE.80.016109Search in Google Scholar

42. SPRS. (2004), “Spatial development strategy of Slovenia”, available at: http://www.mop.gov.si/fileadmin/mop.gov.si/pageuploads/podrocja/prostorski_razvoj/SPRS_angleska_verzija.pdf (6 January 2017).Search in Google Scholar

43. SURS. (2018), “SI-Stat data portal”, available at: http://pxweb.stat.si/pxweb/dialog/statfile1.asp (29 November 2018).Search in Google Scholar

44. Ullman, E. L. (1980), Geography as spatial interaction, University of Washington Press, Seattle.Search in Google Scholar

45. Watts, M. (2009), “Rules versus hierarchy: an application of fuzzy set theory to the assessment of spatial grouping techniques”, in Kolehmainen, M., Toivanen, P., Beliczynski, B. (eds), 9th International Conference on Adaptive and Natural Computing Algorithms, 23-25 April, Springer-Verlag, Berlin Heidelberg, pp. 517-526.10.1007/978-3-642-04921-7_53Search in Google Scholar

46. Watts, M. (2013), “Different spatial grouping algorithms: an application to the design of Australia’s new statistical geography”, Spatial Economic Analysis, Vol. 8, No. 1, pp. 92-112.10.1080/17421772.2012.753637Search in Google Scholar