IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20070083.html

A Matching Model for the Backhaul Problem

Author

Listed:
  • Erhan Demirel

    (Vrije Universiteit Amsterdam)

  • Jos van Ommeren

    (Vrije Universiteit Amsterdam)

  • Piet Rietveld

    (Vrije Universiteit Amsterdam)

Abstract

The ‘backhaul problem’ is characterized by an imbalance in transport flows between locations. This problem is usually studied in a perfectly competitive framework, which essentially predicts that when the imbalance is sufficiently large, the freight price of transport from low demand regions to high demand regions, the so-called backhaul price, drops to zero. This result is inconsistent with empirical observations. In this paper, we develop a matching model to address this inconsistency. We argue that market friction, through search imperfections due to lack of information by carriers on the (future) demand for transport by customers, may play an important role in the determination of backhaul prices. We demonstrate that carriers are at least compensated for the time they search for customers, so the backhaul price is in general positive. The matching model is numerically applied to the inland navigation shipping market in the Rhine river area in Western-Europe. We also analyse the effects of increases in transport costs on transport flows and backhaul prices, e.g. due to climate changes.

Suggested Citation

  • Erhan Demirel & Jos van Ommeren & Piet Rietveld, 2007. "A Matching Model for the Backhaul Problem," Tinbergen Institute Discussion Papers 07-083/3, Tinbergen Institute, revised 19 Dec 2007.
    • Handle: RePEc:tin:wpaper:20070083
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/07083.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Goh, Shao Hung & Chan, Yuxian, 2016. "Operational shadow pricing in back haul container shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 92(C), pages 3-15.
    3. Ishikawa, Jota & Tarui, Nori, 2018. "Backfiring with backhaul problems," Journal of International Economics, Elsevier, vol. 111(C), pages 81-98.
    4. Tsubota, Kenmei, 2015. "Agglomeration and directional imbalance of freight rates : the role of density economies in the transport sector," IDE Discussion Papers 488, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    5. Ming Wu & Xin Li & Yan Chen, 2025. "Port–Shipping Interplay: A Multi-Stage Analysis of Facility Upgrades and Cargo Movement," Mathematics, MDPI, vol. 13(7), pages 1-22, March.
    6. Farren, Dario & Giesen, Ricardo & Rizzi, Luis Ignacio, 2024. "The economics of empty trips," Economics of Transportation, Elsevier, vol. 39(C).
    7. ISHIKAWA, Jota & 石川, 城太 & TARUI, Nori & 樽井, 礼, 2015. "Backfiring with backhaul problems: Trade and Industrial Policies with Endogenous Transport Costs," Discussion paper series HIAS-E-12, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    8. Mundaca, Gabriela, 2024. "Short- and long-term effects of carbon taxation on the prices of products shipped by sea," Energy Policy, Elsevier, vol. 193(C).
    9. Yang,Ron Nan, 2024. "Geographic Imbalance, Search Frictions, and Regulation : Causes of Empty Miles in Freight Trucking," Policy Research Working Paper Series 10775, The World Bank.
    10. Behrens, Kristian & Picard, Pierre M., 2011. "Transportation, freight rates, and economic geography," Journal of International Economics, Elsevier, vol. 85(2), pages 280-291.
    11. Felix L. Friedt & Wesley W. Wilson, 2020. "Trade, transport costs and trade imbalances: An empirical examination of international markets and backhauls," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 592-636, May.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tin:wpaper:20070083. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.