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Regional taxonomy : A comparison of some hierarchic and non-hierarchic strategies

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  • Fischer, Manfred M.

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  • Fischer, Manfred M., 1980. "Regional taxonomy : A comparison of some hierarchic and non-hierarchic strategies," Regional Science and Urban Economics, Elsevier, vol. 10(4), pages 503-537, November.
    • Handle: RePEc:eee:regeco:v:10:y:1980:i:4:p:503-537
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    Cited by:

    1. Michael Peneder, 2003. "Industry Classifications: Aim, Scope and Techniques," Journal of Industry, Competition and Trade, Springer, vol. 3(1), pages 109-129, March.
    2. Juan Carlos Duque & Raúl Ramos & Jordi Suriñach, 2007. "Supervised Regionalization Methods: A Survey," International Regional Science Review, , vol. 30(3), pages 195-220, July.
    3. Marián Halás & Pavel Klapka & Petr Tonev & Marek Bednář, 2015. "An alternative definition and use for the constraint function for rule-based methods of functional regionalisation," Environment and Planning A, , vol. 47(5), pages 1175-1191, May.
    4. Papps, Kerry L. & Newell, James O., 2002. "Identifying Functional Labour Market Areas in New Zealand: A Reconnaissance Study Using Travel-to-Work Data," IZA Discussion Papers 443, Institute of Labor Economics (IZA).
    5. Carlos Mendez & Erick Gonzales, 2021. "Human Capital Constraints, Spatial Dependence, and Regionalization in Bolivia: A Spatial Clustering Approach," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 44(87), pages 115-145.
    6. Juan C. Duque & Nancy Lozano‐Gracia & Jorge E. Patino & Paula Restrepo Cadavid, 2021. "Institutional fragmentation and metropolitan coordination in Latin American cities: Are there links with city productivity?," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1096-1128, August.
    7. Chakraborty, A. & Beamonte, M.A. & Gelfand, A.E. & Alonso, M.P. & Gargallo, P. & Salvador, M., 2013. "Spatial interaction models with individual-level data for explaining labor flows and developing local labor markets," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 292-307.
    8. Shruthi Patil & Leander Kotzur & Detlef Stolten, 2022. "Advanced Spatial and Technological Aggregation Scheme for Energy System Models," Energies, MDPI, vol. 15(24), pages 1-26, December.
    9. Rui Fragoso & Conceição Rego & Vladimir Bushenkov, 2016. "Clustering of Territorial Areas: A Multi-Criteria Districting Problem," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(2), pages 179-198, December.
    10. R. Church & J. C. Duque & D. E. Restrepo, 2020. "The p-Innovation ecosystems model," Papers 2008.05885, arXiv.org.
    11. Daniela Wanek, 2003. "Fuzzy Spatial Analysis Techniques in a Business GIS Environment," ERSA conference papers ersa03p177, European Regional Science Association.
    12. Ana Viñuela‐Jiménez & Fernando Rubiera‐Morollón & Begoña Cueto, 2010. "An Analysis of Urban Size and Territorial Location Effects on Employment Probabilities: The Spanish Case," Growth and Change, Wiley Blackwell, vol. 41(4), pages 495-519, December.
    13. Maria da Conceição Rego & Rui Fragoso & Vladimir Bushenkov, 2014. "Clustering of Territorial Areas: A Multi-Criteria Districting Problem," ERSA conference papers ersa14p218, European Regional Science Association.
    14. Ana Viñuela & Fernando Rubiera-Morollón & Esteban Fernández-Vázquez, 2014. "Applying economic-based analytical regions: a study of the spatial distribution of employment in Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(1), pages 87-102, January.
    15. Robert J. Stimson & William Mitchell & David Rohde & Paul Shyy, 2011. "Using functional economic regions to model endogenous regional performance in Australia: implications for addressing the spatial autocorrelation problem," Regional Science Policy & Practice, Wiley Blackwell, vol. 3(3), pages 131-144, August.
    16. Jing Zhang & Lei Li & Congmou Zhu & Qi Hao & Xinming Chen & Zhoulu Yu & Muye Gan & Wuyan Li, 2023. "Investigating the Spatial Heterogeneity and Influencing Factors of Urban Multi-Dimensional Network Using Multi-Source Big Data in Hangzhou Metropolitan Circle, Eastern China," Land, MDPI, vol. 12(9), pages 1-16, September.

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