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Effects of Macroeconomic Conditions and External Shocks for Port Business: Forecasting Cargo Throughput of Busan Port Using ARIMA and VEC Models

  • Nam, Hyung-Sik (Department of Logistics, Korea Maritime and Ocean University) ;
  • D'agostini, Enrico (Department of International Logistics, Tongmyong University) ;
  • Kang, Dal-Won (Department of Air Transportation & Logistics, Catholic Kwandong University)
  • 투고 : 2022.10.05
  • 심사 : 2022.10.25
  • 발행 : 2022.10.31

초록

The Port of Busan is currently ranked as the seventh largest container port worldwide in terms of cargo throughput. However, port competition in the Far-East region is fierce. The growth rate of container throughput handled by the port of Busan has recently slowed down. In this study, we analyzed how economic conditions and multiple external shocks could influence cargo throughput and identified potential implications for port business. The aim of this study was to build a model to accurately forecast port throughput using the ARIMA model, which could incorporate external socio-economic shocks, and the VEC model considering causal variables having long-term effects on transshipment cargo. Findings of this study suggest that there are three main areas affecting container throughput in the port of Busan, namely the Russia-Ukraine war, the increased competition for transshipment cargo of Chinese ports, and the weaker growth rate of the Korean economy. Based on the forecast, in order for the Port of the Port of Busan to continue to grow as a logistics hub in Northeast-Asia, policy intervention is necessary to diversify the demand for transshipment cargo and maximize benefits of planned infrastructural investments.

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참고문헌

  1. Box, G. E. and Tiao, G. C.(1975). "Intervention analysis with applications to economic and environmental problems". Journal of the American Statistical association, Vol. 70, pp. 70-79. https://doi.org/10.1080/01621459.1975.10480264
  2. Box, G. E., Jenkins, G. M., Reinsel, G. C. and Ljung, G. M.(2015). "Time series analysis: forecasting and control". John Wiley & Sons.
  3. Chung, C. Y. and Song, J. M.(2007),"A Study on the forecast on the port cargo by ANN", Journal of Shipping and Logistics, No. 53, pp. 65-82. https://doi.org/10.37059/TJOSAL.2007..53.65
  4. Chung, Roy C. P., Ip, W. H., and Chan, S. L.(2009), "An ARIMA-intervention analysis model for the financial crisis in China's 27 manufacturing industry". International Journal of Engineering Business Management, Vol. 1, pp. 15-18.
  5. Chung, S. K. and Kim, S. K.(2011), "A Study on the Effect of Changes in Oil Price on Dry Bulk Freight Rates and Intercorrelations between Dry Bulk Freight Rates", Journal of Korea Port Economic Association, Vol. 27, No. 2, pp. 217-240.
  6. Drewry(2021), "Global Container Terminal Operators Annual Review and Forecast 2018", pp. 7-16.
  7. Lai, Sue Ling and Lu, Whei-Li.(2005), "Impact analysis of September 11 on air travel demand in the USA". Journal of Air Transport Management, Vol. 11, No. 6, pp. 455-458. https://doi.org/10.1016/j.jairtraman.2005.06.001
  8. Lee, S. Y. and Ahn, K. Y.(2018), "Study on the Forecasting and Relationship of Busan Cargo by ARIMA and VAR·VEC", Journal of Korean Navigation and Port Research, Vol. 44, No. 1, pp. 44-52.
  9. Lee, S. Y. and Ahn, K. Y.(2020), "Study on the Forecasting and Effecting Factor of BDI by VECM", Journal of Korean Navigation and Port Research, Vol. 42, No. 6, pp. 546-554.
  10. Kim, J. H.(2008), "The Forecast of the Cargo Transportation and Traffic Volume on Container in Gwangyang Port, using Time Series Models", Journal of Korean Navigation and Port Research, Vol. 32, No. 6, pp. 425-431. https://doi.org/10.5394/KINPR.2008.32.6.425
  11. Park, S. Y. and Lee, K. Y.(2002),"A Study on the forecast of container cargo", Journal of Korean Navigation and Port Research, Vol. 26, No. 2, pp. 183-188. https://doi.org/10.5394/KINPR.2002.26.2.183
  12. Park, S.(2021). "Port throughput forecasting using ARIMA and OLS regression: case study: Gwangyang port in Korea"
  13. Rashed, Y., Meersman, H., Van de Voorde, E. and Vanelslander, T.(2017). "Short-term forecast of container throughout: An ARIMA-intervention model for the port of Antwerp". Maritime Economics &Logistics, 19(4), 749-764. https://doi.org/10.1057/mel.2016.8
  14. Shin, C. H., Kang, J. S., Park, S. N. and Lee, J. H.(2008), "A study on the forecast of port traffic using hybrid ARIMA-neural network model", Journal of Korean Navigation and Port Research, Vol. 32, No. 1, pp. 81-88. https://doi.org/10.5394/KINPR.2008.32.1.081