Multicriteria Decision Model for Port Evaluation and Ranking: An Analysis of Container Terminals in Latin America and the Caribbean Using PCA-TOPSIS Methodologies
Source abstract
Abstract
In recent years, despite a decline in international trade and disruptions in the supply chain caused by COVID-19, the main container terminals in Latin America and the Caribbean (LAC) have increased their container volumes. This growth has necessitated significant adaptations by seaports and their authorities to meet new demands. Consequently, there has been a focused analysis on the performance, efficiency, and competitiveness, particularly their most relevant logistical aspects. In this paper, a multi-objective hybrid approach was employed. The Principal Component Analysis (PCA) technique was combined with the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) to rank LAC container terminals and identify operational criteria affecting efficiency. The analysis considered all input variables (berth/quay length, quay draught, yard area, number of quay cranes (portainer), number of yard cranes (trastainer), reachstacker, multicranes, daily montainer movement capacity, number of station reefer container type, number of terminals, and distance to the Panama Canal) and output variable (port performance expressed in TEUs from 2014 to 2023). The results revealed noteworthy findings for several terminals, particularly Colón, Santos, or Cartagena, which stands out as the main container port in LAC not only in annual TEUs throughput, but also in resource utilization.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Maritime Ports and Logistics · Urban and Freight Transport Logistics · Law, logistics, and international trade
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil Engineering, Faculty of Engineering, University of Magdalena (Unimagdalena), Santa Marta 470003, Colombia
Department of Industrial and Civil Engineering, Algeciras School of Engineering and Technology (ASET), University of Cádiz, 11202 Algeciras, Spain
Department of Computer Science Engineering, Algeciras School of Engineering and Technology (ASET), University of Cádiz, 11202 Algeciras, Spain
Faculty of Economic and Business Sciences, Avda. Duque de Nájera s/n, 11002 Cádiz, Spain
References (35)
Show source-provided references
1. Container terminal development in mainland China and its impact on the competitiveness of the port of Hong Kong10.1080/0144164032000122334 ↗
2. Key factors of container port competitiveness: A global shipping lines perspective10.1016/j.marpol.2020.103896 ↗
3. Los vínculos comerciales de América Latina y el Caribe ante los riesgos de fragmentación geopolítica global
4. Assessment of port efficiency within Latin America10.1186/s41072-021-00102-5 ↗
5. Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., and Garau, C. (2022). Computational Science and Its Applications—ICCSA 2022 Workshops. Lecture Notes in Computer Science, Springer International Publishing.10.1007/978-3-031-10562-3 ↗
6. State-of-the-art review on multi-criteria decision-making in the transport sector
7. Assessing the impact of major infrastructure projects on port choice decision: The Colombian case10.1016/j.tra.2018.12.021 ↗
8. Port Competitiveness, Efficiency, and Supply Chains: A Literature Review10.5325/transportationj.58.1.0001 ↗
9. Ližbetin, J., and Stopka, O. (2020). Application of specific mathematical methods in the context of revitalization of defunct intermodal transport terminal: A case study. Sustainability, 12.10.3390/su12062295 ↗
10. Identification of Restricting Criteria for Comprehensive Assessment of Logistics Chains in Intermodal Transport10.2478/logi-2018-0015 ↗
11. Multi-criteria evaluation of railway transport using evaluation method10.2478/logi-2020-0018 ↗
12. Golnar, M., and Beškovnik, B. (2022). A Multi-Criteria Approach for Evaluating a Sustainable Intermodal Transport Chain Affected by the COVID-19 Pandemic. J. Mar. Sci. Eng., 10.10.3390/jmse10111644 ↗
13. A Multi-criteria evaluation of container terminal technologies applying the COPRAS-G method10.3846/16484142.2012.750624 ↗
14. Relationships among port competition, cooperation and competitiveness: A literature review10.1016/j.tranpol.2022.01.014 ↗
15. The drivers of port competitiveness: A critical review10.1080/01441647.2016.1231232 ↗
16. Exploring the drivers of port efficiency in Latin America and the Caribbean10.1016/j.tranpol.2015.09.004 ↗
17. Ilyas, M., Jin, Z., and Ullah, I. (2024). Optimizing Logistics and Transportation Locations in the China–Pakistan Economic Corridor: A Strategic Risk Assessment. Appl. Sci., 14.10.3390/app14051738 ↗
18. The efficiency of container terminals in the northern region of Brazil10.1016/j.jup.2021.101278 ↗
19. An application of AHP on transhipment port selection: A global perspective10.1057/palgrave.mel.9100093 ↗
20. A hybrid Fuzzy AHP-TOPSIS approach for assessing the sustainability of industrial parks
21. Developing a fuzzy TOPSIS approach based on subjective weights and objective weights10.1016/j.eswa.2008.11.035 ↗
22. The efficiency of European container ports: A cross-sectional data envelopment analysis10.1080/13675560500322417 ↗
23. A fuzzy hybrid MCDM approach for professional selection10.1016/j.eswa.2011.09.042 ↗
24. Analysis of a complex of statistical variables into principal components10.1037/h0070888 ↗
25. Jolliffe, I.T. (1986). Principal Component Analysis, Springer.10.1007/978-1-4757-1904-8 ↗
26. A state-of the-art survey of TOPSIS applications10.1016/j.eswa.2012.05.056 ↗
27. Accuracy of the TOPSIS Method with Different Input Data10.1016/j.procs.2022.09.521 ↗
28. A Study on Competitiveness Analysis of Ports in Korea and China by Entropy Weight TOPSIS10.1016/j.ajsl.2016.12.001 ↗
29. Service Quality Evaluation and Ranking of Container terminal Operators10.1016/j.ajsl.2016.12.003 ↗
30. Assessment of provincial waterlogging risk based on entropy weight TOPSIS–PCA method10.1007/s11069-021-04744-3 ↗
31. Multi-superiority response optimization of WEDM for titanium grade-5 using PCA based TOPSIS theory10.1016/j.matpr.2022.04.044 ↗
32. Estimation of remote sensing based ecological index along the Grand Canal based on PCA-AHP-TOPSIS methodology10.1016/j.ecolind.2020.107214 ↗
33. Choosing optimal bunkering ports for liner shipping companies: A hybrid Fuzzy-Delphi–TOPSIS approach10.1016/j.tranpol.2014.04.009 ↗
34. TOPSIS and Modified TOPSIS: A comparative analysis10.1016/j.dajour.2021.100021 ↗
35. Wang, T., Wang, D., and Zeng, Z. (2024). Research on the Construction and Measurement of Digital Governance Level System of County Rural Areas in China—Empirical Analysis Based on Entropy Weight TOPSIS Model. Sustainability, 16.10.3390/su16114374 ↗