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Spatial Dynamics of the Logistics Industry and Implications for Freight Flows

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  • Giuliano, Genevieve
  • Kang, Sanggyun
  • Yuan, Quan

Abstract

This project examines changes in the spatial pattern of warehousing and distribution (W&D) activities. W&D activities are decentralizing in response to rising land values and scale economies. Ultimately, the authors seek to understand whether these spatial shifts result in more truck VMT, or whether the efficiencies gained by larger scale operations allow offsetting savings, such as enabling the use of larger trucks or achieving higher average load factors. Understanding how these shifts are affecting truck VMT is essential for developing effective policies for managing truck VMT and their associated emissions. However, there is no good source for tract or zone level truck flow data, or for intra-metropolitan truck origin-destination data. As a first step, the authors focus on accessibility. From the literature on passenger travel, the authors know that travel distance is related to accessibility. Thus, changes in accessibility to goods markets should be a proxy for goods travel distance, all else equal. The authors examine changes in the spatial pattern of warehousing and distribution activities for the four largest California metropolitan areas: Los Angeles, San Francisco, Sacramento, and San Diego, using ZIP Code Business Patterns data for 2003 and 2013. The authors develop measures of decentralization and concentration. Their results are mixed. When using establishment counts, only Los Angeles shows a consistent pattern of decentralization. There is more evidence of decentralization when using employment counts, which is consistent with larger scale facilities being built at the periphery. Spatial patterns for the largest metro areas are quite different from those of the smaller metro areas. The authors surmise that higher development density and associated land prices push W&D activity to more distant areas. In contrast, W&D location in San Diego and Sacramento is relatively closer to employment, population, and the CBD. If all truck traffic were local, their results suggest possible increases in truck VMT, particularly for the largest metro areas. However, more than half of all commodity flows is non-local. The decentralization the authors observe is likely related to domestic and international trade, for which access to local markets is less important. More research is necessary to determine whether decentralization is a consistent trend in large metro areas, and, if so, whether impacts on truck VMT within metro areas is positive or negative. View the NCST Project Webpage

Suggested Citation

  • Giuliano, Genevieve & Kang, Sanggyun & Yuan, Quan, 2016. "Spatial Dynamics of the Logistics Industry and Implications for Freight Flows," Institute of Transportation Studies, Working Paper Series qt94h6t7s9, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt94h6t7s9
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    References listed on IDEAS

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    Cited by:

    1. Yuan, Quan, 2019. "Does context matter in environmental justice patterns? Evidence on warehousing location from four metro areas in California," Land Use Policy, Elsevier, vol. 82(C), pages 328-338.
    2. Li, Guoqi & Sun, Wenjie & Yuan, Quan & Liu, Sijing, 2020. "Planning versus the market: Logistics establishments and logistics parks in Chongqing, China," Journal of Transport Geography, Elsevier, vol. 82(C).
    3. Yang, Zhiwei & Chen, Xiaohong & Pan, Ruixu & Yuan, Quan, 2022. "Exploring location factors of logistics facilities from a spatiotemporal perspective: A case study from Shanghai," Journal of Transport Geography, Elsevier, vol. 100(C).
    4. Holl, Adelheid & Mariotti, Ilaria, 2018. "Highways and firm performance in the logistics industry," Journal of Transport Geography, Elsevier, vol. 72(C), pages 139-150.
    5. Sakai, Takanori & Kawamura, Kazuya & Hyodo, Tetsuro, 2019. "Evaluation of the spatial pattern of logistics facilities using urban logistics land-use and traffic simulator," Journal of Transport Geography, Elsevier, vol. 74(C), pages 145-160.
    6. 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).
    7. Renata Lúcia Magalhães de Oliveira & Camila Soares Henrique Fontanele Garcia & Paulo Henrique Góes Pinto, 2020. "Accessibility to Food Retailers: The Case of Belo Horizonte, Brazil," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    8. Dubie, Melaku & Kuo, Kai C. & Giron-Valderrama, Gabriela & Goodchild, Anne, 2020. "An evaluation of logistics sprawl in Chicago and Phoenix," Journal of Transport Geography, Elsevier, vol. 88(C).
    9. Yuan, Quan, 2018. "Mega freight generators in my backyard: A longitudinal study of environmental justice in warehousing location," Land Use Policy, Elsevier, vol. 76(C), pages 130-143.
    10. Yuan, Quan & Zhu, Jiren, 2019. "Logistics sprawl in Chinese metropolises: Evidence from Wuhan," Journal of Transport Geography, Elsevier, vol. 74(C), pages 242-252.
    11. Ioannou, Petros, 2018. "Modeling for Local Impact Analysis," Institute of Transportation Studies, Working Paper Series qt7959p38n, Institute of Transportation Studies, UC Davis.

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