Global Hydrogen Export Business Index: An AI-Enhanced Multicriteria Decision Analysis Framework for Assessing Hydrogen Export Potential

Tao Tang, Gordhan Das Valasai, Sajid Mahmood Lakhan, Egemen Sulukan, Abdul Waheed Mahar, Muhammad Alam, Sajjad Bhangwar, Riaz Bhanbhro, Stefano Landini

Research output: Contribution to journalArticlepeer-review

Abstract

Global hydrogen trade is emerging as a central pillar of net-zero strategies, yet there is no unified analytical framework for comparing countries' readiness to export hydrogen. This study develops the Global Hydrogen Export Business Index (GHEBI), an AI-enhanced multicriteria decision analysis (MCDA) framework that evaluates hydrogen export potential across 31 countries. The framework assesses six dimensions that policymakers and investors must consider when designing hydrogen export strategies: (1) resource availability, (2) infrastructure and technology readiness, (3) economic viability, (4) policy and regulatory environment, (5) environmental and social suitability, and (6) geopolitical and geological risk. These dimensions incorporate indicators derived from international datasets and expert consultation. Five established MCDA methods (AHP, TOPSIS, PROMETHEE II, VIKOR, and SAW) are integrated to generate a composite score, while machine-learning models are used to validate ranking stability and identify the most influential determinants. Results show substantial regional disparities: Australia, the United States, and selected Gulf countries lead due to strong renewable resources, port infrastructure, and policy support, whereas Africa and South America score lower because of infrastructure gaps, policy uncertainty, and geohazard exposure. Sensitivity analysis confirms the robustness of rankings to changes in indicator weights. The GHEBI framework offers a transparent, multidimensional tool to guide hydrogen export planning, identify investment priorities, and support the development of resilient and geologically informed hydrogen export pathways.
Original languageEnglish
JournalGeological Journal
DOIs
Publication statusPublished - 7 Jan 2026

Keywords

  • AI-MCDA integration
  • energy resilience
  • export potential
  • hydrogen economy
  • machine learning
  • multicriteria decision analysis
  • resource sustainability

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