Dynamic evaluation of global sustainability: longitudinal ranking and spatial profiling across countries

Area of Science:

• Sustainability Science
• Econometrics
• Environmental Science

Background:

• Static evaluation models limit global sustainability assessment.
• Longitudinal analysis is needed to capture temporal sustainability performance.
• Existing frameworks lack dynamic capabilities for tracking country-level progress.

Purpose of the Study:

• To develop a dynamic analytical framework for global sustainability assessment.
• To trace longitudinal sustainability trajectories across 103 countries from 2014 to 2024.
• To identify key barriers and facilitators of sustainability progress in different country tiers.

Main Methods:

• Integrated framework combining Dynamic TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) with time-decayed entropy weighting.
• Cross-validation of linear rankings using non-linear spatial classification (K-means clustering with k-means++ initialization).
• Utilized seven core indicators across economic, social, and environmental dimensions.

Main Results:

• Identified a pronounced staircase effect in global sustainability, with countries converging into three stable tiers.
• Robustness tests confirmed stable rankings, with no rank reversal among the top 20 countries.
• Lagging Tier countries exhibit environmental efficiency but are constrained by weak human capital and institutional quality.

Conclusions:

• Dynamic sustainability assessment offers an alternative to static rankings, emphasizing temporal evolution.
• Education and governance gaps are critical barriers for lower-tier nations.
• International interventions should address these non-economic factors for effective sustainability progress.