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<p>This paper proposes a novel multi-criteria decision-making (MCDM) framework to analyze the interplay between environmental and financial dimensions in corporate performance. Building on an optimized signal decomposition of the polar factorization, the method calibrates trade-off matrices under alternative scenarios privileging criterion importance, trade-off strength, or balanced relations. Applied to a panel of S&amp;P 500 firms, the approach generates performance scores and entropy-weighted consensus rankings across three classical MCDM methods—TOPSIS, VIKOR, and COPRAS—under nine scenario–method combinations. The empirical results highlight that financial synergies, especially those linking equity, liabilities, assets, and cash flow, dominate across sectors, while environmental and social criteria appear only in specific contexts. ESG variables are structurally linked to firm scale in Basic Materials and Energy, to financing flows in Real Estate, and to decarbonization costs in Utilities, but remain marginal in Financials and Consumer Cyclicals. Negative trade-offs are rare, emerging mainly in tensions between efficiency and scale or responsibility and emissions. Overall, the findings demonstrate that ESG trade-offs in the S&amp;P 500 are sector-contingent, reflecting differences in regulatory exposure, reputational pressure, and operational structure. The proposed framework contributes to both methodology and practice by offering a systematic tool to disentangle the relative weight of financial and environmental criteria in corporate decision-making.</p>

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Environmental and financial performance in the S&P 500: a novel mcdm approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月30日

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  • Marjorie Taboada,
  • Yong Tan,
  • Charbel Jose Chiappetta Jabbour,
  • Peter Wanke

摘要

This paper proposes a novel multi-criteria decision-making (MCDM) framework to analyze the interplay between environmental and financial dimensions in corporate performance. Building on an optimized signal decomposition of the polar factorization, the method calibrates trade-off matrices under alternative scenarios privileging criterion importance, trade-off strength, or balanced relations. Applied to a panel of S&P 500 firms, the approach generates performance scores and entropy-weighted consensus rankings across three classical MCDM methods—TOPSIS, VIKOR, and COPRAS—under nine scenario–method combinations. The empirical results highlight that financial synergies, especially those linking equity, liabilities, assets, and cash flow, dominate across sectors, while environmental and social criteria appear only in specific contexts. ESG variables are structurally linked to firm scale in Basic Materials and Energy, to financing flows in Real Estate, and to decarbonization costs in Utilities, but remain marginal in Financials and Consumer Cyclicals. Negative trade-offs are rare, emerging mainly in tensions between efficiency and scale or responsibility and emissions. Overall, the findings demonstrate that ESG trade-offs in the S&P 500 are sector-contingent, reflecting differences in regulatory exposure, reputational pressure, and operational structure. The proposed framework contributes to both methodology and practice by offering a systematic tool to disentangle the relative weight of financial and environmental criteria in corporate decision-making.