Mapping Non‐Linear ESG Trajectories in OECD Countries: A Topological Entropy Approach

ABSTRACT This study examines the evolution of Environmental, Social and Governance (ESG) performance across 38 OECD countries between 2010 and 2024 using a longitudinal and multi‐dimensional analytical framework. Moving beyond static ESG benchmarking approaches, it investigates how sustainability trajectories evolve under changing institutional, economic and governance conditions. The findings reveal that ESG transitions across advanced economies are neither linear nor uniformly convergent. Instead, countries follow differentiated sustainability pathways characterised by persistent trade‐offs across ESG dimensions. In particular, improvements in governance and social performance do not necessarily coincide with stronger environmental outcomes, highlighting the complexity of balancing competing sustainability priorities under conditions of uncertainty and external shocks. By integrating Multiple Factor Analysis (MFA), Hierarchical Ascending Classification (HAC) and Topological Local Entropy Clustering (TLEC), the analysis provides a dynamic perspective on ESG evolution across OECD countries. The findings contribute to the sustainability strategy literature by emphasising the importance of adaptive and context‐sensitive governance frameworks for managing sustainability transitions. Practical implications are offered for policymakers, firms and investors seeking to strengthen long‐term ESG resilience and sustainability integration strategies.

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Publication Details

Journal
Business Strategy and the Environment
Published
2026-10-06
DOI
https://doi.org/10.1002/bse.71629
Primary Topic
Corporate Social Responsibility Reporting
Type
article
Field-Weighted Citation Impact
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article

Mapping Non‐Linear ESG Trajectories in OECD Countries: A Topological Entropy Approach

Salah Ben Hamad, Rami Ibrahim A. Salem, Sana Gaied Chortane
Business Strategy and the Environment
Corporate Social Responsibility Reporting
article

Mapping Non‐Linear ESG Trajectories in OECD Countries: A Topological Entropy Approach

Salah Ben Hamad, Rami Ibrahim A. Salem, Sana Gaied Chortane
article en

Abstract

ABSTRACT This study examines the evolution of Environmental, Social and Governance (ESG) performance across 38 OECD countries between 2010 and 2024 using a longitudinal and multi‐dimensional analytical framework. Moving beyond static ESG benchmarking approaches, it investigates how sustainability trajectories evolve under changing institutional, economic and governance conditions. The findings reveal that ESG transitions across advanced economies are neither linear nor uniformly convergent. Instead, countries follow differentiated sustainability pathways characterised by persistent trade‐offs across ESG dimensions. In particular, improvements in governance and social performance do not necessarily coincide with stronger environmental outcomes, highlighting the complexity of balancing competing sustainability priorities under conditions of uncertainty and external shocks. By integrating Multiple Factor Analysis (MFA), Hierarchical Ascending Classification (HAC) and Topological Local Entropy Clustering (TLEC), the analysis provides a dynamic perspective on ESG evolution across OECD countries. The findings contribute to the sustainability strategy literature by emphasising the importance of adaptive and context‐sensitive governance frameworks for managing sustainability transitions. Practical implications are offered for policymakers, firms and investors seeking to strengthen long‐term ESG resilience and sustainability integration strategies.

Business Strategy and the Environment
University of Sfax (TN), University of Lancashire (GB), Université Lumière Lyon 2 (FR), University of Doha for Science and Technology (QA), Tunis El Manar University (TN)
Openalex Percentile: Top 8%
Corporate Social Responsibility Reporting
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Mapping Non‐Linear ESG Trajectories in OECD Countries: A Topological Entropy Approach — Salah Ben Hamad, Rami Ibrahim A. Salem, et al. · Business Strategy and the Environment (2026) | TGRS Research Map | TGRS