Uneven Transitions in Container Ship Capacity Across Indo-Pacific Economies (2010–2022): Integrating PCA, ANOVA, and Clustering Evidence
DOI:
https://doi.org/10.59395/ijadis.v7i1.1442Keywords:
Clustering Analysis, Indo-Pacific Shipping, Principal Component Analysis, TEU per Ship, Welch ANOVAAbstract
We examine uneven transitions in container ship capacity (TEU per ship) across five Indo-Pacific economies China, Singapore, Australia, Vietnam, and Indonesia during 20102022 using an integrated statistical framework that combines ANOVA, Welch ANOVA, GamesHowell post-hoc tests, Principal Component Analysis (PCA), and clustering. Results reveal persistent divergence: China and Singapore maintain high-capacity fleets (>10,000 TEU/ship), Australia stabilizes in the mid-tier range (~7,000 TEU/ship), while Indonesia and Vietnam experience rapid but low-level growth (<6,000 TEU/ship). ANOVA confirms significant cross-country differences (F=28.33; p<0.001; 0.65), with Welch ANOVA yielding consistent results under unequal variances (p<0.01). PCA indicates one dominant component (PC199.5%) explaining most variance, forming three readiness clusters: high, medium, and low capacity economies. These patterns suggest that policy inertia, infrastructure bottlenecks, and green transition constraints drive the uneven capacity development. The study contributes by introducing TEU per ship as a cross-national indicator for maritime readiness, linking statistical divergence to SDG targets 8, 9, 10, 13, and 14, and offering empirical guidance for low-carbon fleet transition and port modernization in emerging economies..
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