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The value of specific cargo information for substitutable modes of inland transport

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  • Zhang, Hongtao
  • Lee, Chung-Yee
  • Li, Tian

Abstract

Communication about containers onboard a cargo carrier approaching a harbor with a hinterland operator who is to receive the containers usually reveals the total amount of goods (aggregate number of containers) to be transported inland upon unloading at the arrival dock. This communication is useful for the hinterland operator to plan and deploy its transport capacities. However, further transport of containers on the hinterland involve various transport modes at differing costs. For example, the delivery time requirement of a container dictates the most appropriate mode of inland transport, be it truck, rail, or barge, in decreasing order of speed, flexibility and cost, to move the container to the next destination. In general there may be several types of delivery time requirements and containers of each type is most economically moved inland in a corresponding transport mode. Trucking is usually used for containers that need urgent delivery and train or barge for not so urgent types. In order to efficiently plan the transport capacities for after-arrival conveyance of containers having multi-type delivery time requirements, not only should the aggregate number of containers, but also the number of containers of each type, be made available to the hinterland operator. We consider several information scenarios and in each scenario we solve a single-period capacity planning serving multi-type demands with product substitution. We then compare expected transport costs between information scenarios to evaluate the benefit of specific cargo information in improving the next-step transporting after containers are unloaded at the port of entry.

Suggested Citation

  • Zhang, Hongtao & Lee, Chung-Yee & Li, Tian, 2016. "The value of specific cargo information for substitutable modes of inland transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 23-39.
  • Handle: RePEc:eee:transe:v:85:y:2016:i:c:p:23-39
    DOI: 10.1016/j.tre.2015.10.010
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    1. Tjokroamidjojo, Darsono & Kutanoglu, Erhan & Taylor, G. Don, 2006. "Quantifying the value of advance load information in truckload trucking," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(4), pages 340-357, July.
    2. Bourland, Karla E. & Powell, Stephen G. & Pyke, David F., 1996. "Exploiting timely demand information to reduce inventories," European Journal of Operational Research, Elsevier, vol. 92(2), pages 239-253, July.
    3. Hernández, Salvador & Peeta, Srinivas & Kalafatas, George, 2011. "A less-than-truckload carrier collaboration planning problem under dynamic capacities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 933-946.
    4. DeCroix, Gregory A. & Mookerjee, Vijay S., 1997. "Purchasing demand information in a stochastic-demand inventory system," European Journal of Operational Research, Elsevier, vol. 102(1), pages 36-57, October.
    5. Yehuda Bassok & Ravi Anupindi & Ram Akella, 1999. "Single-Period Multiproduct Inventory Models with Substitution," Operations Research, INFORMS, vol. 47(4), pages 632-642, August.
    6. Thonemann, U. W., 2002. "Improving supply-chain performance by sharing advance demand information," European Journal of Operational Research, Elsevier, vol. 142(1), pages 81-107, October.
    7. Groothedde, Bas & Ruijgrok, Cees & Tavasszy, Lóri, 2005. "Towards collaborative, intermodal hub networks: A case study in the fast moving consumer goods market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(6), pages 567-583, November.
    8. Giannopoulos, G. A., 2004. "The application of information and communication technologies in transport," European Journal of Operational Research, Elsevier, vol. 152(2), pages 302-320, January.
    9. Abacoumkin, Constantinos & Ballis, Athanasios, 2004. "Development of an expert system for the evaluation of conventional and innovative technologies in the intermodal transport area," European Journal of Operational Research, Elsevier, vol. 152(2), pages 410-419, January.
    10. Robert A. Shumsky & Fuqiang Zhang, 2009. "Dynamic Capacity Management with Substitution," Operations Research, INFORMS, vol. 57(3), pages 671-684, June.
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    2. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "OVAP: A strategy to implement partial information sharing among supply chain retailers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 122-136.
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    4. Fan Bu & Heather Nachtmann, 2023. "Literature review and comparative analysis of inland waterways transport: “Container on Barge”," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 140-173, March.

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