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Rail-truck multimodal freight collaboration: a statistical analysis of freight-shipper perspectives

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  • Yuntao Guo
  • Srinivas Peeta
  • Fred Mannering

Abstract

Due to the effects of congestion, capacity reduction of truck-freight carriers, growing freight transportation demand, and increasing social and environmental concerns, there is a critical need for freight shippers to improve shipping quality and reduce transportation costs. Rail-truck multimodal freight collaboration can potentially address this need. In this study, we explore freight-shipper perspectives relating to the factors that may foster or impede their usage of rail-truck multimodal freight collaboration services, and the correlations of their operational and behavioral characteristics with these factors. The study provides insights to rail and truck carriers on collaboration mechanisms that can address the needs of freight shippers, including adopting synergistic technology to improve in-transit visibility, accommodating non-containerized cargo, improving the transshipment process, designing service quality control strategies, and constructing investment and revenue-sharing plans.

Suggested Citation

  • Yuntao Guo & Srinivas Peeta & Fred Mannering, 2016. "Rail-truck multimodal freight collaboration: a statistical analysis of freight-shipper perspectives," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(5), pages 484-506, July.
    • Handle: RePEc:taf:transp:v:39:y:2016:i:5:p:484-506
    DOI: 10.1080/03081060.2016.1174365
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    Cited by:

    1. Tamannaei, Mohammad & Zarei, Hamid & Rasti-Barzoki, Morteza, 2021. "A game theoretic approach to sustainable freight transportation: Competition between road and intermodal road–rail systems with government intervention," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 272-295.
    2. Yanchao Feng & Juan Zhang & Renfu Luo & Yuxi Pan & Shuhai Niu, 2024. "How does the opening of high-speed rail drive energy restructuring? New micro evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    3. Li, Yaping & Guo, Yuntao & Lu, Jian & Peeta, Srinivas, 2019. "Impacts of congestion pricing and reward strategies on automobile travelers’ morning commute mode shift decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 72-88.
    4. Irina V. Benedyk & Srinivas Peeta, 2018. "A binary probit model to analyze freight transportation decision-maker perspectives for container shipping on the Northern Sea Route," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 358-374, September.

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