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Distance-decay functions for daily travel-to-work flows

Author

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  • Halás, Marián
  • Klapka, Pavel
  • Kladivo, Petr

Abstract

The non-homogeneity of geographic space brings about the processes that horizontally relate sections of geographic space, in transport geography referred to as spatial interactions. The distance separating different types of locations plays a crucial role in these interactions. Distance is the major factor that influences the values of interaction intensities. The question is how the intensities decrease with distance, since this decrease is usually not linear. This paper pursues the issues of the shape and parameters of the distance-decay functions based on daily travel-to-work transport movements, taking regional centres in the Czech Republic as the example. First the special distance-decay functions for individual regional centres are presented and discussed, followed by the expression of the universal distance-decay function approximating generally to the traits of the Czech settlement system and the nature of the interaction flows, i.e., travel-to-work. The expression of the universal function is based on the application of two easily accessible variables: population and number of jobs.

Suggested Citation

  • Halás, Marián & Klapka, Pavel & Kladivo, Petr, 2014. "Distance-decay functions for daily travel-to-work flows," Journal of Transport Geography, Elsevier, vol. 35(C), pages 107-119.
    • Handle: RePEc:eee:jotrge:v:35:y:2014:i:c:p:107-119
    DOI: 10.1016/j.jtrangeo.2014.02.001
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    1. A S Fotheringham, 1986. "Modelling Hierarchical Destination Choice," Environment and Planning A, , vol. 18(3), pages 401-418, March.
    2. Cheng, Jianquan & Bertolini, Luca, 2013. "Measuring urban job accessibility with distance decay, competition and diversity," Journal of Transport Geography, Elsevier, vol. 30(C), pages 100-109.
    3. Cassel, Susanna Heldt & Macuchova, Zuzana & Rudholm, Niklas & Rydell, Alexis, 2013. "Willingness to commute long distance among job seekers in Dalarna, Sweden," Journal of Transport Geography, Elsevier, vol. 28(C), pages 49-55.
    4. Jacob J de Vries & Peter Nijkamp & Piet Rietveld, 2009. "Exponential or Power Distance-Decay for Commuting? An Alternative Specification," Environment and Planning A, , vol. 41(2), pages 461-480, February.
    5. Murat Celik, H. & Guldmann, Jean-Michel, 2007. "Spatial interaction modeling of interregional commodity flows," Socio-Economic Planning Sciences, Elsevier, vol. 41(2), pages 147-162, June.
    6. Ibeas, Ángel & Cordera, Ruben & dell’Olio, Luigi & Coppola, Pierluigi, 2013. "Modelling the spatial interactions between workplace and residential location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 110-122.
    7. Johansson, Börje & Klaesson, Johan & Olsson, Michael, 2002. "On the non-linearity of the willingness to commute," ERSA conference papers ersa02p476, European Regional Science Association.
    8. Börje Johansson & Johan Klaesson & Michael Olsson, 2002. "Time distances and labor market integration," Papers in Regional Science, Springer;Regional Science Association International, vol. 81(3), pages 305-327.
    9. A G Wilson, 1971. "A Family of Spatial Interaction Models, and Associated Developments," Environment and Planning A, , vol. 3(1), pages 1-32, March.
    10. Gutiérrez, Javier & Cardozo, Osvaldo Daniel & García-Palomares, Juan Carlos, 2011. "Transit ridership forecasting at station level: an approach based on distance-decay weighted regression," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1081-1092.
    11. Langford, M. & Higgs, G. & Fry, R., 2012. "Using floating catchment analysis (FCA) techniques to examine intra-urban variations in accessibility to public transport opportunities: the example of Cardiff, Wales," Journal of Transport Geography, Elsevier, vol. 25(C), pages 1-14.
    12. Martínez, L. Miguel & Viegas, José Manuel, 2013. "A new approach to modelling distance-decay functions for accessibility assessment in transport studies," Journal of Transport Geography, Elsevier, vol. 26(C), pages 87-96.
    13. Morton E O'Kelly & Michael A Niedzielski, 2009. "Are Long Commute Distances Inefficient and Disorderly?," Environment and Planning A, , vol. 41(11), pages 2741-2759, November.
    14. Mozolin, M. & Thill, J. -C. & Lynn Usery, E., 2000. "Trip distribution forecasting with multilayer perceptron neural networks: A critical evaluation," Transportation Research Part B: Methodological, Elsevier, vol. 34(1), pages 53-73, January.
    15. Mamun, Sha A. & Lownes, Nicholas E. & Osleeb, Jeffrey P. & Bertolaccini, Kelly, 2013. "A method to define public transit opportunity space," Journal of Transport Geography, Elsevier, vol. 28(C), pages 144-154.
    16. S Openshaw & C J Connolly, 1977. "Empirically Derived Deterrence Functions for Maximum Performance Spatial Interaction Models," Environment and Planning A, , vol. 9(9), pages 1067-1079, September.
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