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Modelling cyclic container freight index using system dynamics

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  • Jun-Woo Jeon
  • Okan Duru
  • Gi-Tae Yeo

Abstract

This paper investigates the cyclical nature of container shipping market represented by a containerized freight index and proposes a predictive cyclical model of the market. In contrast to the traditional spectral analysis (univariate), system dynamics reflect the drivers of the market in both supply and demand side, and therefore, it is a multi-variate system equilibrium approach consisting of various causal spillovers from sub-components of the market. This study is the first to analyze the cycle of container market using system dynamics. By utilizing system dynamics cyclicality approach, one-step ahead predictions are generated for monthly containerized freight index and compared to conventional benchmarks for post-sample validation. Our study can also help policymakers and shipping liners for better management and invest timing of container ship.

Suggested Citation

  • Jun-Woo Jeon & Okan Duru & Gi-Tae Yeo, 2020. "Modelling cyclic container freight index using system dynamics," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(3), pages 287-303, April.
    • Handle: RePEc:taf:marpmg:v:47:y:2020:i:3:p:287-303
    DOI: 10.1080/03088839.2019.1708984
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    Cited by:

    1. Zhao, Hong-Mei & He, Hong-Di & Lu, Kai-Fa & Han, Xiao-Long & Ding, Yi & Peng, Zhong-Ren, 2022. "Measuring the impact of an exogenous factor: An exponential smoothing model of the response of shipping to COVID-19," Transport Policy, Elsevier, vol. 118(C), pages 91-100.
    2. Bai, Xiwen & Zhang, Xiunian & Li, Kevin X. & Zhou, Yaoming & Yuen, Kum Fai, 2021. "Research topics and trends in the maritime transport: A structural topic model," Transport Policy, Elsevier, vol. 102(C), pages 11-24.

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