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A logit model for shipment size choice with latent classes – Empirical findings for Germany

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  • Piendl, Raphael
  • Liedtke, Gernot
  • Matteis, Tilman

Abstract

Decisions on shipment size in freight transport are often seen to represent a whole set of logistics decisions made by shippers and recipients. Also, shipment sizes have a large impact on transport mode choice. Therefore, they are an important aspect in the modeling of freight transport demand, as they allow to display the reactions of various stakeholders on policy measures. In this article, a model for the discrete choice of shipment sizes is applied to interregional road freight transport. Preferences of actors are reflected by a total logistics cost expression. Furthermore, a Latent Class Analysis approach is applied to identify groups of transport cases with similar logistics requirements. The classification reduces significantly heterogeneity in behavior. Reactions of actors on external influences such as policy measures could be predicted more accurately.

Suggested Citation

  • Piendl, Raphael & Liedtke, Gernot & Matteis, Tilman, 2017. "A logit model for shipment size choice with latent classes – Empirical findings for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 188-201.
    • Handle: RePEc:eee:transa:v:102:y:2017:i:c:p:188-201
    DOI: 10.1016/j.tra.2016.08.023
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    References listed on IDEAS

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    1. Abate, Megersa & de Jong, Gerard, 2014. "The optimal shipment size and truck size choice – The allocation of trucks across hauls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 262-277.
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    Citations

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    Cited by:

    1. Raphael Piendl & Martin Koning & François Combes & Gernot Liedtke, 2022. "Building latent segments of goods to improve shipment size modeling: Confirmatory evidence from France," Post-Print hal-04117547, HAL.
    2. Jiang, Xiaodan & Fan, Houming & Luo, Meifeng & Xu, Zhenlin, 2020. "Strategic port competition in multimodal network development considering shippers’ choice," Transport Policy, Elsevier, vol. 90(C), pages 68-89.
    3. Piendl, Raphael & Matteis, Tilman & Liedtke, Gernot, 2019. "A machine learning approach for the operationalization of latent classes in a discrete shipment size choice model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 149-161.
    4. Odolinski, Kristofer & Ek, Karin, 2024. "Estimating the impact of transport costs on firms’ choice of transport chain and shipment size," Working Papers 2024:5, Swedish National Road & Transport Research Institute (VTI).
    5. Günay, Gürkan, 2023. "Shipment size and vehicle choice modeling for road freight transport: A geographical perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    6. Khakdaman, Masoud & Rezaei, Jafar & Tavasszy, Lóránt A., 2020. "Shippers’ willingness to delegate modal control in freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    7. Verena Maria Stockhammer & Sarah Pfoser & Karin Markvica & Jürgen Zajicek & Matthias Prandtstetter, 2021. "Behavioural Biases Distorting the Demand for Environmentally Friendly Freight Transport Modes: An Overview and Potential Measures," Sustainability, MDPI, vol. 13(21), pages 1-34, October.

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