Comparative Analysis of Global University Ranking Dynamics: A Multi-Metric Evaluation of Performance Shifts
This study presents a multi-metric analysis of the QS World University Rankings by Subject 2026: Engineering & Technology, examining ranking structure, temporal movement between 2025 and 2026, country-level concentration, and indicator-level performance across the leading universities. The dataset contains 2025 and 2026 ranks, overall score, and five core QS indicators: academic reputation, employer reputation, citations, H-index, and international research network (IRN). The results show a highly concentrated global landscape, with the United States contributing 22 universities, while China, the United Kingdom, and Australia each contribute 8 universities. At the institutional level, the score distribution is steep at the top and compressed in the lower part of the list, led by MIT (95.9), Stanford University (93.5), and ETH Zurich (92.7), indicating that relatively small score differences can separate many lower-ranked institutions.The comparative analysis shows strong temporal stability, with a Pearson correlation of r = 0.946 between the 2025 and 2026 rankings, despite visible upward and downward mobility among a subset of institutions. Country-level results further reveal asymmetric national profiles: Switzerland records the strongest average ranking position (7.5) and highest average score (90.4), while Singapore achieves the highest employer reputation (92.8), citations (95.8), and H-index (94.8) among the top-performing countries. Volatility analysis indicates that China (STD = 16.2) and Australia (STD = 14.9) exhibit the largest cross-institutional rank fluctuations. Correlation analysis confirms that overall score is most strongly associated with 2026 rank (r ≈ -0.93), followed by academic reputation (r ≈ -0.80) and employer reputation (r ≈ -0.75), whereas citations (r ≈ -0.34), H-index (r ≈ -0.53), and IRN show weaker direct effects. Overall, the findings demonstrate that elite university performance is shaped by a combination of strong reputation, research impact, and national concentration, rather than by a single dominant metric.
