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Multicriteria evaluation of competitiveness of container terminals in the Baltic Sea region

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: After the outbreak of the covid-19 pandemic and Russo-Ukrainian war, the situation in the Baltic Sea Region (BSR) changed, especially regarding maritime container terminals. The aim of the article is to identify major Baltic container terminals and to perform a multicriteria analysis of their competitiveness. The analysis will be carried out before (2019) and after (2022) the turmoil on the market in question. Design/methodology/approach: The study uses the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II) with subjective criteria weights, as well as the entropy method with objective criteria weights. Findings: The obtained results show that two Polish maritime container terminals, DCT Gdańsk and GCT Gdynia, as well as Finnish Vuossari can be assessed as the most competitive both in 2019 and 2022. At the same time, in the analyzed years, the lowest positions in the rankings were maintained by Swedish GCT Gavle and Vasthamnen, Finnish Euroports Finland as well as Latvian BCT Riga. Research limitations/implications: Limited data availability influenced the choice of criteria used in the study. Moreover, website data sources used in the study may result in the inaccuracy of our calculations. Finally, the subjectivity involved in the selection of chosen criteria and some of their weights could lead to different competitiveness assessment results of maritime container terminals in the BSR. Practical implications: Our findings should be of interest to terminal operators and managers planning their strategy for next years, especially if they want to maintain their competitive advantage in the region after the lifting of sanctions imposed on Russian ports. Originality/value: This is the first paper to compare the multicriteria rankings of competitiveness before and after the turmoil on the BSR container market, especially as industry reports and research on the BSR usually consider the annual results achieved by individual ports, ignoring the efficiency of the terminals that comprise them.
Rocznik
Tom
Strony
9--26
Opis fizyczny
Bibliogr. 27 poz.
Twórcy
  • Department of Operational Research, Faculty of Economics and Sociology, University of Lodz
  • Department of Operational Research, Faculty of Economics and Sociology, University of Lodz
Bibliografia
  • 1. Acer, A., Yanginlar, G. (2017). The Determination of Turkish Container Ports Performance with TOPSIS Multiple Criteria Decision Making Method. Journal of Management, Marketing and Logistics-JMML, 4(2), pp. 67-75. doi: 10.17261/Pressacademia.2017.
  • 2. Al-Aomar, R. (2010). A combined AHP-entropy method for deriving subjective and objective criteria weights. International Journal of Industrial Engineering: Theory, Applications and Practice, 17(1), pp. 2-12.
  • 3. Bartosiewicz, A. (2020). Application of the AHP and PROMETHEE II methods to the evaluation of the competitiveness of Polish and Russian Baltic container terminals. Pomorstvo. Scientific Journal of Maritime Research, 34(1), pp. 102-110. doi: 10.31217/P.34.1.12.
  • 4. Bartosiewicz, A., Jadczak, R. (2023). Multi-criteria Analysis of the Competitiveness of Major Baltic Sea Container Terminals. Comparative Economic Research. Central and Eastern Europe, 26, pp. 116.
  • 5. Bartosiewicz, A., Szterlik, P. (2021). Small container terminals in the Baltic Sea region: an overview and multi-criteria analysis of competitiveness. Journal of Baltic Studies, 52(4), pp. 503-520. doi: 10.1080/01629778.2021.1965634.
  • 6. Bruno, M. (2022). Global Ports container throughput collapses as Russia-Ukraine war rages on. Retrieved from: https://www.porttechnology.org/news/global-ports-container- throughput-collapses-as-russia-ukraine-war-rages-on/, 14.06.2023.
  • 7. Dyck, G.K. van, Ismael, H.M. (2015). Multi-Criteria Evaluation of Port Competitiveness in West Africa Using Analytic Hierarchy Process (AHP). American Journal of Industrial and Business Management, 5(6), pp. 432-446. doi: 10.4236/AJIBM.2015.56043.
  • 8. Global Ports Investments PLC (2023). Q4 and FY 2022 Operational results. Retrived from: https://www.globalports.com/en/investors/news/20230117/, 14.06.2023.
  • 9. Guy, E., Urli, B. (2006). Port Selection and Multicriteria Analysis: An Application to the Montreal-New York Alternative. Maritime Economics & Logistics, 8(2), pp. 169-186. doi: 10.1057/PALGRAVE.MEL.9100152.
  • 10. Kobryń, A. (2014). Multi-criteria decision support in space management. Warsaw: Difin.
  • 11. Lee, S. et al. (2014). A Study on the Comparative Analysis of Port Competitiveness Using AHP. KMI International Journal of Maritime Affairs and Fisheries, 6(1), pp. 53-71. doi: 10.54007/IJMAF.2014.6.1.53.
  • 12. Liu, D.-C. et al. (2020). Use of the Fuzzy AHP-TOPSIS Method to Select the Most Attarctive Container Port. Journal of Marine Science and Technology, 28(2), pp. 92-104. doi: 10.6119/JMST.202004_28(2).0003.
  • 13. Madeira, A.G. et al. (2012). Multicriteria and multivariate analysis for port performance evaluation. International Journal of Production Economics, 140(1), pp. 450-456. doi: 10.1016/J.IJPE.2012.06.028.
  • 14. Notteboom, T. (2021). Top 15 containers ports in Europe in 2020. Retrived from: https://www.porteconomics.eu/top-15-containers-ports-in-europe-in-2020/, 5.12.2021.
  • 15. Pamucar, D., Faruk Gorçün, О. (2022). Evaluation of the European container ports using a new hybrid fuzzy LBWA-CoCoSo’B techniques. Expert Systems with Applications, 203. doi: 10.1016/J.ESWA.2022.117463.
  • 16. Qin, J. et al. (2022). ORESTE-SORT: a novel multiple criteria sorting method for sorting port group competitiveness. Annals of Operations Research, pp. 1-35. doi: 10.1007/S10479-022-04991-Y.
  • 17. Saaty, T.L. (2004). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. New York: McGraw-Hill.
  • 18. Shannon, C. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27, pp. 379-423.
  • 19. Synak, E., Ołdakowski, B. (2020). Baltic ports with a decrease in turnovers in the first half of 2020. Gdynia: Port Monitor.
  • 20. Teng, J.-Y., Huang, W.-C., Huang, M.-J. (2004). Multicriteria Evaluation for Port Competitiveness of Eight East Asian Container Ports. Journal of Marine Science and Technology, 12(4), pp. 256-264. doi: 10.51400/2709-6998.2245.
  • 21. Trzaskalik, T. (2009). Multi-criteria methods in the Polish financial market. Warsaw: PWN.
  • 22. UNCTAD (2021). Review of Maritime Report 2021 (UNCTAD/RMT/2021). Geneva: United Nations Publications.
  • 23. Wang, Q.-F. et al. (2018). Evaluation of the Key Development Factors for the Shanghai Cruise Tourism Industry Using an Interval-Valued Fuzzy Number Method. Journal of Marine Science and Technology, 26(4), pp. 508-517. doi: 10.6119/JMST. 201808_26(4).0004.
  • 24. Zhang, X., Wu, Y. (2023). Analysis of public transit operation efficiency based on multi-source data: A case study in Brisbane, Australia. Research in Transportation Business and
  • Management, 46, pp. 1-10. doi: 10.1016/j.rtbm.2022.100859.
  • 25. Ziajka, E., Rozmarynowska-Mrozek, M. (2021). Cargo turnover in Top 10 Baltic ports. Rebound after tough 2020. Gdynia: Port Monitor.
  • 26. Ziajka, E., Rozmarynowska-Mrozek, M. (2022). Results of Top 10 Baltic Container Ports in first half of 2022. Gdynia: Port Monitor.
  • 27. Ziajka, E., Rozmarynowska-Mrozek, M. (2023). Impact of the geopolitical situation on the largest Baltic ports in 2022. Gdynia: Port Monitor.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-da6271a6-aac1-4f72-aa8c-2f76ce12dca0
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