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Time-dependent patterns in freight trip generation

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  • Holguín-Veras, José
  • Ramirez-Rios, Diana
  • Pérez-Guzmán, Sofía

Abstract

This paper summarizes the research conducted by the authors to investigate time-dependent patterns in Freight Trip Generation (FTG). As part of the research, the authors estimated econometric FTG models as a function of establishment attributes and temporal variables, using multi-year establishment-level data collected during the period 2005–2014. These unique data—encompassing the period of economic turmoil around the 2008 collapse of Wall Street, and the period of recovery that followed—were collected in New York City from commercial establishments in various industry sectors. The comprehensive modeling effort undertaken considered four different functional forms, two combinations of establishment characteristics, two different metrics of time, and eleven different industry sectors defined by two-digits North-America Industry Classification System (NAICS). The resulting models were analyzed to assess the extent and magnitude of the time-dependent effects on FTG for the industry sectors in the sample. In its final sections, the paper discusses the implications for transportation planning and policy and summarizes the chief findings of the effort.

Suggested Citation

  • Holguín-Veras, José & Ramirez-Rios, Diana & Pérez-Guzmán, Sofía, 2021. "Time-dependent patterns in freight trip generation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 423-444.
    • Handle: RePEc:eee:transa:v:148:y:2021:i:c:p:423-444
    DOI: 10.1016/j.tra.2021.03.029
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    References listed on IDEAS

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    1. André Romano Alho & João Abreu e Silva, 2017. "Modeling retail establishments’ freight trip generation: a comparison of methodologies to predict total weekly deliveries," Transportation, Springer, vol. 44(5), pages 1195-1212, September.
    2. Pani, Agnivesh & Sahu, Prasanta K., 2019. "Planning, designing and conducting establishment-based freight surveys: A synthesis of the literature, case-study examples and recommendations for best practices in future surveys," Transport Policy, Elsevier, vol. 78(C), pages 58-75.
    3. Gunn, Hugh, 0. "Spatial and temporal transferability of relationships between travel demand, trip cost and travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 163-189, April.
    4. Holguín-Veras, José & Aros-Vera, Felipe & Browne, Michael, 2015. "Agent interactions and the response of supply chains to pricing and incentives," Economics of Transportation, Elsevier, vol. 4(3), pages 147-155.
    5. Iván Sánchez-Díaz & José Holguín-Veras & Xiaokun Wang, 2016. "An exploratory analysis of spatial effects on freight trip attraction," Transportation, Springer, vol. 43(1), pages 177-196, January.
    6. Pani, Agnivesh & Sahu, Prasanta K. & Chandra, Aitichya & Sarkar, Ashoke K., 2019. "Assessing the extent of modifiable areal unit problem in modelling freight (trip) generation: Relationship between zone design and model estimation results," Journal of Transport Geography, Elsevier, vol. 80(C).
    7. Iván Sánchez-Díaz & José Holguín-Veras & Xiaokun Wang, 2016. "An exploratory analysis of spatial effects on freight trip attraction," Transportation, Springer, vol. 43(1), pages 177-196, January.
    8. Pani, Agnivesh & Sahu, Prasanta K. & Patil, Gopal R. & Sarkar, Ashoke K., 2018. "Modelling urban freight generation: A case study of seven cities in Kerala, India," Transport Policy, Elsevier, vol. 69(C), pages 49-64.
    9. McCarthy, Patrick S., 1982. "Further evidence on the temporal stability of disaggregate travel demand models," Transportation Research Part B: Methodological, Elsevier, vol. 16(4), pages 263-278, August.
    10. Danièle Patier & Jean-Louis Routhier, 2008. "How to Improve the Capture of Urban Goods Movement Data?," Post-Print halshs-00328991, HAL.
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