Dineswary Nadarajan of SEGi University, along with co-authors Elayaraja Aruchunan and Noor Fadiya Mohd Noor, has made a significant contribution to the field of maritime transportation and global port analytics through their latest publication in PLOS ONE (July 30, 2024), titled: “New Clusterization of Global Seaport Countries Based on Their DEA and FDEA Network Efficiency Scores.”
The study introduces a novel clustering framework that redefines how global seaport efficiency is evaluated and grouped. Using Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) as core performance metrics, the authors examined the Liner Shipping Connectivity Index (LSCI) in combination with GDP across 133 countries to assess the performance of global maritime networks.
Recognising the limitations of traditional clustering models in maritime transport literature, the research applies both k-means and hierarchical clustering techniques, ultimately validating hkmeans as the most effective method for grouping countries based on network efficiency.
The resulting clusters were classified into four newly established groups:
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Low Connectivity (LC) – 24 countries
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Medium Connectivity (MC) – 47 countries
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High Connectivity (HC) – 40 countries
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Very High Connectivity (VHC) – 22 countries
These findings represent the first empirical attempt to cluster countries based on DEA and FDEA-derived maritime network efficiency scores, offering both clarity and strategic value for policymakers, industry stakeholders, investors, and researchers in maritime logistics, transportation infrastructure, and trade facilitation.
The inclusion of fuzzy data enhances the adaptability of the clustering process, confirming the practicality and consistency of hkmeans in forming meaningful groups for broad datasets.
Implications and Impact
This research marks a step forward in data-driven maritime policy development. It provides actionable insights into the connectivity status of global seaports, facilitating improved strategic planning, resource allocation, and international collaboration in the logistics and transport sectors.
By integrating rigorous mathematical modelling with practical maritime metrics, Dineswary and her co-researchers provide a robust foundation for predictive analytics, policy alignment, and investor confidence in the global maritime economy.
Read the full research: https://doi.org/10.1371/journal.pone.0305146