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A destination choice model for very large gas carriers (VLGC) loading from the US Gulf

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  • Bai, Xiwen
  • Lam, Jasmine Siu Lee

Abstract

This study is one of the first to model energy shipping destination choice behaviors and identify their associations with various market factors from charterers' perspective. The paper uses very large gas carriers loading from the US Gulf as an illustration. Attributes include freight rate, propane price spread, bunker costs and number of ships in the destination areas. It also identifies the effects of the Panama Canal expansion on destination choices, by dividing sample data into two sub-periods: pre- and post-expansion. Furthermore, both aggregate and disaggregate analysis for different ports are provided. This work draws significant implications for energy transport planning. Understanding the charterer's choice of destinations is vital in determining traffic flow to a specific destination and in forecasting supply patterns. This model can be applied to other downstream commodity shipping segments with available arbitrage opportunities, less sticky trade flows and active traders.

Suggested Citation

  • Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A destination choice model for very large gas carriers (VLGC) loading from the US Gulf," Energy, Elsevier, vol. 174(C), pages 1267-1275.
    • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:1267-1275
    DOI: 10.1016/j.energy.2019.02.148
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    Cited by:

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    2. Javier Ho & Paul Bernal, 2021. "Estimating a global demand model for soybean traffic through the Panama Canal," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-23, December.
    3. Yin, Yuwei & Lam, Jasmine Siu Lee, 2022. "Bottlenecks of LNG supply chain in energy transition: A case study of China using system dynamics simulation," Energy, Elsevier, vol. 250(C).
    4. Bai, Xiwen & Ma, Zhongjun & Zhou, Yaoming, 2023. "Data-driven static and dynamic resilience assessment of the global liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    5. Li, Yiliang & Bai, Xiwen & Wang, Qi & Ma, Zhongjun, 2022. "A big data approach to cargo type prediction and its implications for oil trade estimation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    6. Michail Nektarios A. & Melas Konstantinos D., 2022. "Geopolitical Risk and the LNG-LPG Trade," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 28(3), pages 243-265, September.
    7. Bai, Xiwen & Cheng, Liangqi & Iris, Çağatay, 2022. "Data-driven financial and operational risk management: Empirical evidence from the global tramp shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).

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