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<p>This study presents a structured decision-making framework for assessing green mergers and acquisitions (M&amp;A) by integrating environmental, social, and governance (ESG) performance with financial return thresholds. Drawing on seven high-profile renewable energy transactions executed between 2020 and 2025, the research applies a four-quadrant analytical model comprising the <i>M&amp;A-ESG Fit Matrix</i>, <i>Capital Allocation Heatmap</i>, <i>IRR–ESG Frontier Graph</i>, and <i>Policy Roadmap Timeline</i>. This framework operationalises the <i>IRR_min</i> constraint aligned with investor mandates and applies Pareto frontier optimisation to identify deals that maximise ESG impact without compromising financial competitiveness. The empirical analysis reveals that transactions positioned on the efficient frontier consistently deliver superior value by balancing sustainability outcomes with robust internal rates of return. The approach aligns with global strategic consulting methodologies, enhancing transparency, capital efficiency, and policy alignment in deal selection. While the study is constrained by data availability, limited sample size, and sectoral concentration in renewables, it offers a replicable template for broader application across industries. Future research should incorporate longitudinal post-acquisition performance tracking, sector-adjusted ESG taxonomies, and dynamic risk modelling. The proposed framework helps bridge the gap between ESG ambitions and disciplined investment performance, providing actionable insights for investors, policymakers, and corporate strategists navigating the evolving green M&amp;A landscape.</p>

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Advancing green business expansion through strategic mergers and acquisitions leveraging sustainability and government policy for enhanced innovation and resilience

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月19日

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  • Piyush Choudhary,
  • Nikunj Kumar Jain,
  • Pratyush Yadav

摘要

This study presents a structured decision-making framework for assessing green mergers and acquisitions (M&A) by integrating environmental, social, and governance (ESG) performance with financial return thresholds. Drawing on seven high-profile renewable energy transactions executed between 2020 and 2025, the research applies a four-quadrant analytical model comprising the M&A-ESG Fit Matrix, Capital Allocation Heatmap, IRR–ESG Frontier Graph, and Policy Roadmap Timeline. This framework operationalises the IRR_min constraint aligned with investor mandates and applies Pareto frontier optimisation to identify deals that maximise ESG impact without compromising financial competitiveness. The empirical analysis reveals that transactions positioned on the efficient frontier consistently deliver superior value by balancing sustainability outcomes with robust internal rates of return. The approach aligns with global strategic consulting methodologies, enhancing transparency, capital efficiency, and policy alignment in deal selection. While the study is constrained by data availability, limited sample size, and sectoral concentration in renewables, it offers a replicable template for broader application across industries. Future research should incorporate longitudinal post-acquisition performance tracking, sector-adjusted ESG taxonomies, and dynamic risk modelling. The proposed framework helps bridge the gap between ESG ambitions and disciplined investment performance, providing actionable insights for investors, policymakers, and corporate strategists navigating the evolving green M&A landscape.