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2023 Journal Impact Factor - 0.7
2023 CiteScore - 1.4
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
A Simplified Forecasting Model for the Estimation of Container Traffic in Seaports at a National Level – the Case of Poland
1 Gdynia Maritime University, Gdynia, Poland
Times cited (SCOPUS): 4
ABSTRACT: Comprehensive forecasting of future volumes of container traffic in seaports is important when it comes to port development, including investments, especially in relation to costly transport infrastructure (e.g. new terminals). The aim of this article is to present a specific, simplified model of demand forecasting for container traffic in seaports as well as to give a practical verification of the model in the Polish seaport sector. The model consists of relevant indexes of containerisation (values, dynamics) referring to the macroeconomic characteristics of the country of cargo origin as well as destination-predictor variables (e.g. population, foreign trade, gross domestic product). This method will facilitate the evaluation of three basic segments of the container market: foreign trade services, maritime transit flows and land transit flows. International comparisons of indexes (benchmarking) as well as extrapolations of future changes can support this prediction process. A practical implementation of this research has enabled us to calculate that the total container volume in Poland will be approximately 4.69 – 4.87 million TEU by the year 2023.
KEYWORDS: Container, Containerization, TEU, Polish Seaport Sector, Simplified Forecasting Model, Container Traffic in Seaports, Estimation of Container Traffic in Seaports, Estimation of Container Traffic
REFERENCES
Chen, S. H. and Chen, J. N. (2010) ‘Forecasting container throughputs at ports using genetic programming’, Expert Systems with Applications. Elsevier Ltd, 37(3), pp. 2054–2058. doi: 10.1016/j.eswa.2009.06.054. - doi:10.1016/j.eswa.2009.06.054
Chou, C. C., Chu, C. W. and Liang, G. S. (2008) ‘A modified regression model for forecasting the volumes of Taiwan’s import containers’, Mathematical and Computer Modelling, 47(9–10), pp. 797–807. doi: 10.1016/j.mcm.2007.05.005. - doi:10.1016/j.mcm.2007.05.005
Darabi, S. and Suljevic, M. (2015) ‘Forecasting Process for Predicting Container Volumes in the Shipping Industry’.
Diaz, R., Talley, W. and Tulpule, M. (2011) ‘Forecasting empty container volumes’, Asian Journal of Shipping and Logistics, 27(2), pp. 217–236. doi: 10.1016/S2092-5212(11)80010-6. - doi:10.1016/S2092-5212(11)80010-6
Gokkus, Ü., Sinan Yildirim, M. and Akoglu, K. (2015) ‘Prediction of the Container Traffic in a Seaport Stockyard Using Genetic Algorithm’, 7(03), pp. 9–15.
Gökkuş, Ü., Yildirim, M. S. and Aydin, M. M. (2017) ‘Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports’, Discrete Dynamics in Nature and Society, 2017. doi: 10.1155/2017/2984853. - doi:10.1155/2017/2984853
Gosasang, V., Chandraprakaikul, W. and Kiattisin, S. (2011) ‘A comparison of traditional and neural networks forecasting techniques for container throughput at bangkok port’, Asian Journal of Shipping and Logistics, 27(3), pp. 463–482. doi: 10.1016/S2092-5212(11)80022-2. - doi:10.1016/S2092-5212(11)80022-2
Huang, A. et al. (2015) ‘An interval knowledge based forecasting paradigm for container throughput prediction’, Procedia Computer Science. Elsevier Masson SAS, 55(Itqm), pp. 1381–1389. doi: 10.1016/j.procs.2015.07.126. - doi:10.1016/j.procs.2015.07.126
Huang, A., Qiao, H. and Wang, S. (2014) ‘Forecasting container throughputs with domain knowledge’, Procedia Computer Science. Elsevier Masson SAS, 31(Itqm), pp. 648–655. doi: 10.1016/j.procs.2014.05.312. - doi:10.1016/j.procs.2014.05.312
Iannone, R. et al. (2016) ‘Proposal for a flexible discrete event simulation model for assessing the daily operation decisions in a Ro-Ro terminal’, Simulation Modelling Practice and Theory. Elsevier B.V., 61, pp. 28–46. doi: 10.1016/j.simpat.2015.11.005. - doi:10.1016/j.simpat.2015.11.005
Jensen, M. (2014) Forecasting Container Cargo Throughput in Ports, Erasmus University Rotterdam.
Kotcharat, P. (2016) ‘The Maritime Commons: Digital Repository of the World A forecasting model for container throughput: empirical research for Laem Chabang Port , Thailand Kingdom of Thailand’.
KRILE, S., MAIOROV, N. and FETISOV, V. (2018) ‘Forecasting the Operational Activities of the Sea Passenger Terminal Using Intelligent Technologies’, Transport Problems, 13(1), pp. 27–36. doi: 10.21307/tp.2018.13.1.3. - doi:10.21307/tp.2018.13.1.3
Lappalainen, A. (2013) ‘Scenario-based traffic forecast for routes between the penta ports in 2020’, Publication from the Centre for Maritime Studies, University of Turku, A65.
Peng, W. Y. and Chu, C. W. (2009) ‘A comparison of univariate methods for forecasting container throughput volumes’, Mathematical and Computer Modelling. Elsevier Ltd, 50(7–8), pp. 1045–1057. doi: 10.1016/j.mcm.2009.05.027. - doi:10.1016/j.mcm.2009.05.027
Population projection at national level (2015-2080) (2019) Eurostat, https://ec.europa.eu/eurostat/data/database.
Rahman, N. S. F. A., Muridan, M. and Najib, A. F. A. (2015) ‘A Maritime Forecasting Method for Analysing the Total Cargo Handling at Johor Port Berhad from 2013 to 2020’, 6(3), pp. 187–193.
Rashed, Y. et al. (2018) ‘A combined approach to forecast container throughput demand: Scenarios for the Hamburg-Le Havre range of ports’, Transportation Research Part A: Policy and Practice. Elsevier, 117(July 2016), pp. 127–141. doi: 10.1016/j.tra.2018.08.010. - doi:10.1016/j.tra.2018.08.010
Statistical Yearbook of Maritime Economy (2018) Statistic Poland. Statistical Office in Szczecin, Warsaw/Szczecin.
World Economic Outlook Database, October 2018 (2018) IMF, https://www.imf.org/external/pubs/ft/weo/2018/02/weodata/index.aspx.
Citation note:
Matczak M.: A Simplified Forecasting Model for the Estimation of Container Traffic in Seaports at a National Level – the Case of Poland. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 14, No. 1, doi:10.12716/1001.14.01.18, pp. 153-158, 2020