Environmental, Social and Governance (ESG) Drivers of Sustainability Transitions in Sub‐Saharan Africa
Why One Size Does Not Fit All
Bibliographic Data
| ID | 22418458 |
|---|---|
| Authors | Emmanuel Kwaku Manu (0000-0002-6233-3981, UNE Business School, Faculty of Science, Agriculture, Business and Law University of New England Armidale New South Wales Australia, corresponding author), Bismark Asante (0009-0002-8719-3580, UNE Business School, Faculty of Science, Agriculture, Business and Law University of New England Armidale New South Wales Australia), Gabriel Eweje (0000-0003-4210-2489, School of Business and Law Edith Cowan University Perth Western Australia Australia) |
| Year | 2026 |
| Publication date | 2026-07-14 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Business Strategy and the Environment (JOURNAL) |
| Journal identifiers | ISSN: 0964-4733 • E-ISSN: 1099-0836 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/bse.71275 |
| OpenAlex | W7168237067 |
| Language | EN |
| References cited | 33 |
Despite growing emphasis on sustainability transitions in developing economies, evidence remains limited on how environmental, social and governance (ESG) conditions shape sustainability outcomes in sub‐Saharan Africa (SSA). This study examines the environmental, social and governance drivers of sustainability transition performance across 39 SSA countries over the period 2000–2023. A composite sustainability transition performance index (STPI), constructed from renewable energy consumption and reverse‐coded energy intensity indicators, is used to capture transition performance. A multi‐method panel framework is employed to examine direct, conditional, nonlinear and dynamic relationships. The findings show that environmental pressures, particularly carbon intensity and energy use, consistently weaken sustainability transition performance, whereas labour‐market conditions, particularly female employment and female wage employment, improve sustainability outcomes. Governance conditions operate primarily through regulatory quality, which significantly conditions the relationship between environmental pressures and sustainability transition performance. In addition, GDP per capita shapes the sustainability effects of environmental and labour‐market drivers across countries. Nonlinear estimates reveal an inverted U‐shaped relationship between energy use and sustainability transition performance, while dynamic estimates indicate strong persistence over time. The findings reveal substantial heterogeneity in sustainability pathways, suggesting that one‐size‐fits‐all sustainability policies may be less effective in SSA and underscoring the importance of context‐specific ESG strategies. The study contributes to sustainability‐transition research by demonstrating how interacting ESG drivers shape heterogeneous sustainability transitions in SSA.
Corporate governance · Energy transition · Environmental Sustainability Index · Per capita · Social sustainability · Sustainability · Sustainability organizations · Economic Growth and Development · Energy, Environment, Economic Growth · Environmental Sustainability in Business
Handbook on Constructing Composite Indicators
Financial development and energy consumption in Central and Eastern European frontier economies
Economic growth, CO 2 emissions, renewable waste and FDI relation in Pakistan
Sustainability transitions in the making
A review on Environmental Kuznets Curve hypothesis using bibliometric and meta-analysis
Trade openness–carbon emissions nexus
The effect of urbanization on CO2 emissions in emerging economies
Carbon dioxide abatement in Africa
How to do Xtabond2
Women Empowerment and Economic Development
Sustainability transitions
Economic Growth and the Environment
The multi-level perspective on sustainability transitions
From riches to digitalization
The Worldwide Governance Indicators
The impact of environmental policy, technological innovations, and digitalisation
Natural resource abundance, governance, and government expenditure
Achieving environmental sustainability in Africa
Understanding Interaction Models
What To Do (and Not to Do) with Time-Series Cross-Section Data
| Highly cited | No |
|---|