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Estimating an origin-destination table for US imports of waterborne containerized freight

Author

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  • Levine, Brian
  • Nozick, Linda
  • Jones, Dean

Abstract

Containerized freight imports into the US are growing at an average of 10% per year. This traffic is concentrated at a small number of US seaports. It is therefore important to have an accurate understanding of the flow of containers from their origin country through these seaports to their final destination. This paper develops an optimization model to estimate route flows and a corresponding multi-modal origin-destination table for containers by synthesizing data on international trade and railcar movements with a gravity model for the demand of container traffic. This analysis provides insights into the balance of rail and truck inland transportation from each port.

Suggested Citation

  • Levine, Brian & Nozick, Linda & Jones, Dean, 2009. "Estimating an origin-destination table for US imports of waterborne containerized freight," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(4), pages 611-626, July.
    • Handle: RePEc:eee:transe:v:45:y:2009:i:4:p:611-626
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    Citations

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    Cited by:

    1. Likun Wang & Anne Goodchild & Yong Wang, 2018. "The effect of distance on cargo flows: a case study of Chinese imports and their hinterland destinations," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 456-475, September.
    2. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Chen, Yan & Song, Dongdong & Zhi, Danyue & Wang, Yiyun & Gao, Ziyou, 2023. "Estimating intercity heavy truck mobility flows using the deep gravity framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    3. Martinez, Camil & Steven, Adams B. & Dresner, Martin, 2016. "East Coast vs. West Coast: The impact of the Panama Canal’s expansion on the routing of Asian imports into the United States," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 274-289.
    4. da Silva, Marcelino Aurélio Vieira & de Almeida D’Agosto, Marcio, 2013. "A model to estimate the origin–destination matrix for soybean exportation in Brazil," Journal of Transport Geography, Elsevier, vol. 26(C), pages 97-107.
    5. Guerrero, David, 2014. "Deep-sea hinterlands: Some empirical evidence of the spatial impact of containerization," Journal of Transport Geography, Elsevier, vol. 35(C), pages 84-94.
    6. Jin, Jiahuan & Ma, Mingyu & Jin, Huan & Cui, Tianxiang & Bai, Ruibin, 2023. "Container terminal daily gate in and gate out forecasting using machine learning methods," Transport Policy, Elsevier, vol. 132(C), pages 163-174.
    7. Kalahasthi, Lokesh & Holguín-Veras, José & Yushimito, Wilfredo F., 2022. "A freight origin-destination synthesis model with mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    8. Kashiha, Mona & Thill, Jean-Claude & Depken, Craig A., 2016. "Shipping route choice across geographies: Coastal vs. landlocked countries," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 1-14.
    9. Tiller, Kara Carroll & Thill, Jean-Claude, 2017. "Spatial patterns of landside trade impedance in containerized South American exports," Journal of Transport Geography, Elsevier, vol. 58(C), pages 272-285.
    10. Jones, Dean A. & Farkas, Julie L. & Bernstein, Orr & Davis, Chad E. & Turk, Adam & Turnquist, Mark A. & Nozick, Linda K. & Levine, Brian & Rawls, Carmen G. & Ostrowski, Scott D. & Sawaya, William, 2011. "U.S. import/export container flow modeling and disruption analysis," Research in Transportation Economics, Elsevier, vol. 32(1), pages 3-14.
    11. Huang, Dong & Grifoll, Manel & Sanchez-Espigares, Jose A. & Zheng, Pengjun & Feng, Hongxiang, 2022. "Hybrid approaches for container traffic forecasting in the context of anomalous events: The case of the Yangtze River Delta region in the COVID-19 pandemic," Transport Policy, Elsevier, vol. 128(C), pages 1-12.

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