The Influence of the Zonation Effect on a System of Hierarchical Functional Regions

1. Brown, P. J. B., Hincks, S. (2008), “A Framework for Housing Market Area Delineation: Principles and Application”, Urban Studies, Vol. 45, No. 11, pp. 2225-2247.10.1177/0042098008095866Search in Google Scholar

2. Brown, P. J. B., Pitfield, D. E. (1990), “The Intramax derivation of commodity market structures from freight flow data”, Transportation Planning and Technology, Vol. 15, No. 1, pp. 59-81.10.1080/03081069008717440Search in Google Scholar

3. Drobne, S. (2016), “Model vrednotenja števila in območij funkcionalnih regij” (“A Model Evaluating the Number and Areas of Functional Regions”; in Slovene only), Doctoral thesis, University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana.Search in Google Scholar

4. Drobne, S., Bogataj, M. (2014), “Regions for Servicing Old People: Case study of Slovenia”, Business systems research journal, Vol. 5, No. 3, pp. 19-36.10.2478/bsrj-2014-0017Search in Google Scholar

5. Drobne, S., Bogataj, M. (2015), “Optimal allocation of public service centres in the central places of functional regions”, in 15th IFAC/IEEE/IFIP/IFORS Symposium on Information Control Problems in Manufacturing, INCOM 2015, IFAC, Ottawa, pp. 2449-2454.10.1016/j.ifacol.2015.06.441Search in Google Scholar

6. Drobne, S., Lakner, M. (2017), “A concept of SM-measure to compare hierarchical clustering”, in Zadnik Stirn, L. et al. (Eds.), SOR '17 proceedings, Slovenian Society Informatika, Section for Operational Research, Ljubljana, pp. 308-313.Search in Google Scholar

7. Fowlkes, E. B., Mallows, C. L. (1983), “A Method for Comparing Two Hierarchical Clusterings”, Journal of the American Statistical Association, Vol. 78, No. 383, pp. 553-569.10.1080/01621459.1983.10478008Search in Google Scholar

8. Gehlke, C. E., Biehl, K. (1934), “Certain effects of grouping upon the size of the correlation coefficient in census tract material”, Journal of the American Statistical Association, Vol. 29, No. 185a, pp. 169-170.Search in Google Scholar

9. Hubert, L., Arabie, P. (1985), “Comparing partitions”, Journal of Classification, Vol. 2, pp. 193-218.10.1007/BF01908075Search in Google Scholar

10. Jaccard, P. (1912), “The distribution of the flora in the Alpine Zone”, New Phytologist, Vol. 11, No. 2, pp. 37-50.10.1111/j.1469-8137.1912.tb05611.xSearch in Google Scholar

11. Jaegal, Y. (2013), “Delineating Housing Market Areas in the Seoul Metropolitan Area Using a Geo-Computational Approach”, Journal of the Association of Korean Geographers, Vol. 2, No. 1, pp. 7-20.10.25202/JAKG.2.1.2Search in Google Scholar

12. Jenko, D., Drobne, S. (2014), “Modeliranje prostorskih vzorcev delovne mobilnosti in selitev z vektorskimi polji” (“Modelling commuting and migration patterns using vector fields”; in Slovene only), in Ciglič, R., Perko, D., Zorn, M. (Eds.), Digitalni prostor, GIS v Sloveniji, 12, ZRC, Ljubljana, pp. 163-171.Search in Google Scholar

13. Johansson, B. (1998), “Infrastructure, Market Potential and Endogenous Growth”, Jönköping International Business School, Jönköping (Mimeo).Search in Google Scholar

14. 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

15. Kohl, T., Brouver, A. E. (2014), “The Development of Trade Blocs in an Era of Globalisation”, Environment and Planning A, Vol. 46, No. 7, pp. 1535-1553.10.1068/a46261Search in Google Scholar

16. Koo, H. (2012), “Improved Hierarchical Aggregation Methods for Functional Regionalization in the Seoul Metropolitan Area”, Journal of the Korean Cartographic Association, Vol. 12, No. 2, pp. 25-35.Search in Google Scholar

17. Landré, M., Håkansson, J. (2013), “Rule versus Interaction Function: Evaluating Regional Aggregations of Commuting Flows in Sweden”, European Journal of Transport and Infrastructure Research, Vol. 13, No. 1, pp. 1-19.Search in Google Scholar

18. Li, T., Ogihara, M., Sheng, M. (2004), “On Combining Multiple Clusterings”, Proceedings of the ACM Conference on Information and Knowledge Management, Vol. 13, pp. 294-303.10.1145/1031171.1031234Search in Google Scholar

19. 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

20. 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

21. Meila, M., Heckerman, D. (1999), “An Experimental Comparison of Model-based Clustering Methods”, Proceedings of the Conference on Knowledge Discovery and Data Mining, pp. 16-22.Search in Google Scholar

22. Mirkin, B. G. (1996), “Mathematical classification and clustering”, Kluwer Academic Press.10.1007/978-1-4613-0457-9Search in Google Scholar

23. Mitchell, W., Baum, S., Flanagan, M., Hannan, M. (2013). “CofFEE Functional Economic Regions”, available at: http://e1.newcastle.edu.au/coffee/functional_regions/ (18 November 2015).Search in Google Scholar

24. Openshaw, S. (1984), “The Modifiable Areal Unit Problem”, Geobooks, Norwich.Search in Google Scholar

25. Rand, W. M. (1971), “Objective Criteria for the Evaluation of Clustering Methods”, Journal of the American Statistical Association, Vol. 66, No. 336, pp. 846-850.10.1080/01621459.1971.10482356Search in Google Scholar

26. Romano, S., Vinh, N. X., Bailey, J., K. Verspoor (2016), “Adjusting for Chance Clustering Comparison Measures”, Journal of Machine Learning Research, Vol. 17, pp. 1-32.Search in Google Scholar

27. SMARS (2016), “Digital data on territorial units of Slovenia, Data on municipalities, the Surveying and Mapping Authority of the Republic Slovenia, Ljubljana”, available at: http://www.gu.gov.si/en/services/free_access_database/ (15January 2016).Search in Google Scholar

28. SORS (2016), “Persons in employment (excluding farmers) by municipalities of residence and municipalities of workplace by sex, municipalities, Slovenia, annually), the Statistical office of the Republic Slovenia, Ljubljana”, available at: http://pxweb.stat.si/pxweb/Dialog/varval.asp?ma=0723405E&ti=&path=../Database/Demographics/07_labour_force/05_labour_force_register/10_07234_working_migrations/&lang=1 (15 January 2016).Search in Google Scholar

29. Stillwell, J., Daras, K., Bell, M., Lomax, N. (2014), “The IMAGE Studio: A tool for internal migration analysis and modelling”, Applied Spatial Analysis and Policy, Vol. 7, No. 1, pp. 5-23.10.1007/s12061-014-9104-4Search in Google Scholar

30. van Dongen, S. (2000), “Performance Criteria for Graph Clustering and Markov Cluster Experiments”, Technical Report INS-R0012, Centrum voor Wiskunde en Informatica.Search in Google Scholar

31. Vinh, N. X., Epps, J., Bailey, J. (2010), “Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance”, The Journal of Machine Learning Research, Vol. 11, pp. 2837-2854.Search in Google Scholar

32. Wagner, S., Wagner, D. (2007), “Comparing Clusterings - An Overview”, Technical Report 2006-04, Faculty of Informatics, University of Karlsruhe.Search in Google Scholar

33. Wallace, D. L. (1983), “A Method for Comparing Two Hierarchical Clusterings: Comment”, Journal of the American Statistical Association, Vol. 78, No. 383, pp. 569-576.10.2307/2288118Search in Google Scholar

• Dashboard for the Management and Acceptance of Customer Orders
• Using EPP Boxes in a Dark Store: A New Approach to Simplify Food Retail E-Commerce Deliveries
• Circular Economy and Consumer’s Engagement: An Exploratory Study on Higher Education
• Internal Logistics Process Improvement using PDCA: A Case Study in the Automotive Sector
• Migration Flows through the Lens of Human Resource Ageing
• Boosting Regional Socioeconomic Development through Logistics Activities: A Conceptual Model
• Possible Impact of Risk Management Strategies with Farm Model on a Mixed Farm Type
• Conflict and Corporate Social Responsibility in Duopoly
• Editorial for the Special Issue: “Novel Solutions and Novel Approaches in Operational Research”: co-published with the Slovenian Society INFORMATIKA – Section for Operational Research (SSI-SOR)
• The Risk and Return of Traditional and Alternative Investments Under the Impact of COVID-19
• A Machine Learning Approach to Forecast International Trade: The Case of Croatia