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COVID-19 상황을 고려한 Shanghai Containerized Freight Index 예측

Shanghai Containerized Freight Index prediction considering the COVID-19

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초록

본 연구는 COVID-19 상황을 고려한 컨테이너 운임예측(SCFI)을 연구의 목적으로 한다. SCFI 예측을 위해 System dynamics를 활용했다. 활용된 변수는 SCFI, 중국의 컨테이너 수출물동량, 전 세계 선박 공급량, 글로벌 선사의 정시성이다. 분석 결과, SCFI에 물동량과 컨테이너 공급량이 미치는 영향이 COVID-19 전과 후가 다른 것으로 분석되었다. COVID-19 전후의 물동량이 SCFI에 미치는 영향 정도는 각각 0.281123, 1.12893으로 분석되었다. COVID-19 전후의 컨테이너 선박 공급량이 SCFI 미치는 영향 정도는 각각 1.16042, 2.97813으로 분석되어, COVID-19 기간에 컨테이너 선박의 공급량이 SCFI 미치는 영향이 증가한 것으로 분석되었다. COVID-19 회복 후에 글로벌 선사의 정시성 회복으로 컨테이너 운임은 감소하는 것으로 나타났으며, 2023년에 최저점을 기록하지만, 예전 수준의 운임하락은 없는 것으로 분석되었다.

Abstract

The purpose of this study is to predict container freight rates, considering COVID-19 situation. This paper utilized SCFI for container freight rates and employed System dynamics in order to predict. SCFI, China's container trade volumes, and global ship supply were used as variables. In addition, global schedule reliability was used to reflect the COVID-19 situation. It was discovered that effects of trade volume and container supply on SCFI were different before and after COVID-19. The trade volume affected on SCFI by 0.281123 before COVID-19, while affected on SCFI by 1.12893 after COVID-19 respectively. Meanwhile, container ship supply was analyzed to influence 1.12893 and 2.97813, before and after COVID-19 and it was shown that the effect of container ship supply on SCFI increased after COVID-19. Furthermore, it was predicted that container freight rates would decrease as global schedule reliability recovers along with COVID-19 recovery.

참고문헌 (25)

  1. 전준우, "China Containerized Freight Index가 컨테이너 선가에 영향을 미치는 시차 분석", 해운물류연구, 36(4), pp.655~675 (2020), 한국해운물류학회[DOI]
  2. Aslani, A., "Role of renewable energy policies in energy dependency in Finland: System dynamics approach", Applied energy, 113, pp.758~765 (2014)
  3. Barber, P., "Forecasting the need for medical specialists in Spain: application of a system dynamics model", Human resources for health, 8(1), pp.1~9 (2010)
  4. Batchelor, R., "Forecasting spot and forward prices in the international freight market", International Journal of Forecasting, 23(1), pp.101~114 (2007)
  5. Chen, S. Meersman, H., "Forecasting spot rates at main routes in the dry bulk market", Maritime Economics & Logistics, 14(4), pp.498~537 (2012)
  6. Clarkson Research, "Clarksons Forecast Club. 2021. 3", ~ (2021)
  7. Cullinane, K., "A short-term adaptive forecasting model for BIFFEX speculation: a Box—Jenkins approach", Maritime Policy & Management, 19(2), pp.91~114 (1992)
  8. Cullinane, K. P. B., "A comparison of models for forecasting the Baltic freight index: Box-Jenkins revisited", International journal of maritime economics, 1(2), pp.15~39 (1999)
  9. Dikos, G., "Niver lines: a system-dynamics approach to tanker freight modeling", Interfaces, 36(4), pp.326~341 (2006)
  10. Fan, L., "Analyzing ship investment behaviour in liner shipping", Maritime Policy & Management, 40(6), pp.511~533 (2013)
  11. Forrester, J. W., "Industrial dynamics: a major breakthrough for decision makers", Harvard business review, 36(4), pp.37~66 (1958)
  12. Geman, H., "Shipping markets and freight rates: an analysis of the Baltic Dry Index", The Journal of Alternative Investments, 15(1), pp.98~109 (2012)
  13. Jeon, J. W., "Modelling cyclic container freight index using system dynamics", Maritime Policy & Management, 47(3), pp.287~303 (2020)
  14. Jeon, J. W., "System Dynamics in the Predictive Analytics of Container Freight Rates", Transportation Science, 55(4), pp.815~967 (2021)
  15. Nikola KUTIN, "Study of the Optimal Timing of Container Ship Orders Considering the Uncertain Shipping Environment", The Asian Journal of Shipping and Logistics, 33(2), pp.85~93 (2017), 한국해운물류학회
  16. Lewis, C. D., "A practical guide to exponential smoothing and curve fitting" (1982), Butterworth-Heinemann
  17. Munim, Z. H., "Forecasting container shipping freight rates for the Far East–northern Europe trade lane", Maritime Economics & Logistics, 19(1), pp.106~125 (2017)
  18. Randers, J., "Forecasting turning points in shipping freight rates: lessons from 30 years of practical effort", System Dynamics Review: The Journal of the System Dynamics Society, 23(2-3), pp.253~284 (2007)
  19. Scarsi, R., "The bulk shipping business: market cycles and shipowners’ biases", Maritime Policy & Management, 34(6), pp.577~590 (2007)
  20. Stopford, M., "Maritime economics 3e" (2009), Routledge
  21. Suryani, E., "Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework", Expert Systems with Applications, 37(3), pp.2324~2339 (2010)
  22. Yeo, G. T., "Analysis of Dynamic Effects on Seaports Adopting Port Security Policy", Transportation Research Part A: Policy and Practice, 49, pp.285~301 (2013)
  23. Veenstra, A. W., "A co-integration approach to forecasting freight rates in the dry bulk shipping sector", Transportation Research Part A: policy and practice, 31(6), pp.447~458 (1997)
  24. Vetitnev, A., "System dynamics modelling and forecasting health tourism demand: the case of Russian resorts", Current Issues in Tourism, 19(7), pp.618~623 (2016)

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