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A comparison of Euclidean Distance, Travel Times, and Network Distances in Location Choice Mixture Models

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  • Sabina Buczkowska

    (IFSTTAR/AME/DEST - Dynamiques Economiques et Sociales des Transports - IFSTTAR - Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux - Communauté Université Paris-Est)

  • Nicolas Coulombel

    (LVMT - Laboratoire Ville, Mobilité, Transport - IFSTTAR - Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux - UPEM - Université Paris-Est Marne-la-Vallée - ENPC - École nationale des ponts et chaussées)

  • Matthieu de Lapparent

    (IFSTTAR/AME/DEST - Dynamiques Economiques et Sociales des Transports - IFSTTAR - Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux - Communauté Université Paris-Est)

Abstract

This article investigates the selection of a distance measure in location modeling. While in the empirical literature the choice usually boils down to picking one single measure, this research proposes a flexible approach in which several measures may be used in parallel to capture the surrounding economic landscape. This is intended to acknowledge that interactions between agents may take several forms, occurring through different channels and as such being based on different measures. The methodology is applied to the location choice of establishments in the Paris region, using a mixture of ”mono-distance” hurdle-Poisson models. Seven distance measures are considered: Euclidean distance, the travel times by car (for the peak and off-peak periods) and by public transit, and the corresponding network distances. For all the economic sectors considered, the mixture of hurdle-Poisson models performs significantly better than the “pure” mono-distance models. This corroborates that local spatial spillovers are indeed channeled by different means, hence best represented using several measures. The combination of peak and off-peak road travel times (slightly) outperforms other combinations including the Euclidean distance, supporting the choice of meaningful over more abstract measures in spatial econometric models. The distance measure most likely to capture local spatial spillovers varies depending on the economic sector examined, reflecting differences between sectors in operations and location choice criteria.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Sabina Buczkowska & Nicolas Coulombel & Matthieu de Lapparent, 2019. "A comparison of Euclidean Distance, Travel Times, and Network Distances in Location Choice Mixture Models," Post-Print hal-02392996, HAL.
  • Handle: RePEc:hal:journl:hal-02392996
    DOI: 10.1007/s11067-018-9439-5
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    Cited by:

    1. Xiaoqian Sun & Sebastian Wandelt & Mark Hansen, 2020. "Airport Road Access at Planet Scale using Population Grid and Openstreetmap," Networks and Spatial Economics, Springer, vol. 20(1), pages 273-299, March.
    2. Milad Malekzadeh & Jed A. Long, 2024. "Mobility deviation index: incorporating geographical context into analysis of human mobility," Journal of Geographical Systems, Springer, vol. 26(3), pages 427-448, July.
    3. Ruggeri, Aurora & Di Liddo, Felicia & Gabrielli, Laura & Tajani, Francesco & Morano, Pierluigi, 2025. "What is the “best” way to measure the relative location variables in the market value assessment? An econometric method applied to an Italian case study," Land Use Policy, Elsevier, vol. 148(C).
    4. Ceccarelli Valentina & Correani Luca & Morganti Patrizio, 2024. "Heterogeneity and geographical location in Italian Business Networks," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 51(4), pages 793-814, December.
    5. Fabien Tricoire & Sophie N. Parragh & Margaretha Gansterer, 2024. "The hiking tourist problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(2), pages 183-207, June.
    6. Chengzhuo Wu & Li Zhuo & Zhuo Chen & Haiyan Tao, 2021. "Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index," Sustainability, MDPI, vol. 13(14), pages 1-17, July.

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