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The geography of warehouses in the São Paulo Metropolitan Region and contributing factors to this spatial distribution

Author

Listed:
  • Léonardo Guerin

    (Polytechnic School [São Paulo] - USP - Universidade de São Paulo = University of São Paulo)

  • José Geraldo Vidal Vieira

    (UFSCar - Federal University of São Carlos)

  • Renata Lúcia Magalhães de Oliveira

    (CEFET-MG - Centro Federal de Educação Tecnológica de Minas Gerais)

  • Leise Kelli de Oliveira

    (UFMG - Universidade Federal de Minas Gerais = Federal University of Minas Gerais [Belo Horizonte, Brazil])

  • Henrique Ewbank de Miranda Vieira

    (Faculdade de Engenharia de Sorocaba)

  • Laetitia Dablanc

    (LVMT - Laboratoire Ville, Mobilité, Transport - ENPC - École des Ponts ParisTech - Université Gustave Eiffel)

Abstract

This paper aims to characterize the relocation of warehouses in the São Paulo Metropolitan Region (SPMR) considering the spatial structure of changes in warehouse locations. We also discuss the potential factors that could attract warehouses to their location, especially in peripheral regions. The study encompasses the period between 1992 and 2017 and analyzes the influence of geographical, economics, road infrastructure, municipality service tax rate, cargo theft, and real estate prices on logistics facility location. The results show no evidence of logistics sprawl in SPMR during the studied period, although a small sprawl appeared between 2010 and 2017, moving the barycenter to the Northwestern direction of the SPMR. The main factors that influence the decision to move the warehouses are the low cost of land, lower tax, and a well-served infrastructure with highway intersections. There is a positive spatial correlation between warehouse per capita and cargo theft.

Suggested Citation

  • Léonardo Guerin & José Geraldo Vidal Vieira & Renata Lúcia Magalhães de Oliveira & Leise Kelli de Oliveira & Henrique Ewbank de Miranda Vieira & Laetitia Dablanc, 2021. "The geography of warehouses in the São Paulo Metropolitan Region and contributing factors to this spatial distribution," Post-Print hal-03565703, HAL.
    • Handle: RePEc:hal:journl:hal-03565703
    DOI: 10.1016/j.jtrangeo.2021.102976
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    Citations

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    Cited by:

    1. Liang, Xinrui & Fan, Shiqi & Lucy, John & Yang, Zaili, 2022. "Risk analysis of cargo theft from freight supply chains using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Wang, Kailai & Chen, Zhenhua & Cheng, Long & Zhu, Pengyu & Shi, Jian & Bian, Zheyong, 2023. "Integrating spatial statistics and machine learning to identify relationships between e-commerce and distribution facilities in Texas, US," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    3. Wu, Jishi & Feng, Tao & Jia, Peng & Li, Gen, 2024. "Spatial allocation of heavy commercial vehicles parking areas through geo-fencing," Journal of Transport Geography, Elsevier, vol. 117(C).
    4. Trent, Nadia M. & Joubert, Johan W., 2022. "Logistics sprawl and the change in freight transport activity: A comparison of three measurement methodologies," Journal of Transport Geography, Elsevier, vol. 101(C).
    5. Beatriz Torres Silva & Mauro Sampaio, 2023. "Factors influencing cargo robbery in last-mile delivery of e-commerce: an empirical study in Brazil," Journal of Transportation Security, Springer, vol. 16(1), pages 1-30, December.

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