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The rationale behind and effects of Bunker Adjustment Factors

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  • Wang, Dong-Hua
  • Chen, Chung-Ching
  • Lai, Cheng-Sheng

Abstract

The Bunker Adjustment Factor (BAF) system was first introduced following the oil shocks of the 1970s. The underlying justification for such a system was that shipping lines operating in freight conferences could not otherwise adjust their prices promptly enough to counteract the devastating effect of bunker price increases. Thirty years after its imposition, BAF has always been a bone of contention between carriers and shippers. Ocean carriers contend that it is a necessary evil to reduce their exposure to volatile bunker price, while shippers argue that this risk should either be considered as a normal commercial venture, or dealt with in a more transparent way. When bunker surcharges began to climb in 2003, BAF disputes became one of the main obstacles to the dialog between both parties. To settle the dispute over BAF, the Europe Commission (EC) called for the submission on the issue of surcharges.

Suggested Citation

  • Wang, Dong-Hua & Chen, Chung-Ching & Lai, Cheng-Sheng, 2011. "The rationale behind and effects of Bunker Adjustment Factors," Journal of Transport Geography, Elsevier, vol. 19(4), pages 467-474.
  • Handle: RePEc:eee:jotrge:v:19:y:2011:i:4:p:467-474
    DOI: 10.1016/j.jtrangeo.2009.11.002
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    References listed on IDEAS

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    1. Marlow, Peter & Nair, Rawindaran, 2006. "Liner shipping and information exchange--a European perspective," Marine Policy, Elsevier, vol. 30(6), pages 681-688, November.
    2. Pierre Cariou & Francois-Charles Wolff, 2006. "An Analysis of Bunker Adjustment Factors and Freight Rates in the Europe/Far East Market (2000–2004)," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(2), pages 187-201, June.
    3. Amir Alizadeh & Manolis Kavussanos & David Menachof, 2004. "Hedging against bunker price fluctuations using petroleum futures contracts: constant versus time-varying hedge ratios," Applied Economics, Taylor & Francis Journals, vol. 36(12), pages 1337-1353.
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    Cited by:

    1. Ziaul Haque Munim & Hans-Joachim Schramm, 0. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 0, pages 1-18.
    2. Slack, Brian & Gouvernal, Elisabeth, 2011. "Container freight rates and the role of surcharges," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1482-1489.
    3. Ziaul Haque Munim & Hans-Joachim Schramm, 2017. "Forecasting container shipping freight rates for the Far East – Northern Europe trade lane," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 106-125, March.
    4. Christian Finnsgård & Joakim Kalantari & Zeeshan Raza & Violeta Roso & Johan Woxenius, 2018. "Swedish shippers’ strategies for coping with slow-steaming in deep sea container shipping," Journal of Shipping and Trade, Springer, vol. 3(1), pages 1-24, December.
    5. Finnsgård, Christian & Kalantari, Joakim & Roso, Violeta & Woxenius, Johan, 2020. "The Shipper's perspective on slow steaming - Study of Six Swedish companies," Transport Policy, Elsevier, vol. 86(C), pages 44-49.
    6. Dong-Hua Wang, 2014. "Ocean shipping deregulation restructures the liner shipping industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(1), pages 97-111, January.
    7. Ziaul Haque Munim & Hans-Joachim Schramm, 2021. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 310-327, June.

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