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Carbon Emissions and Firm Profitability: A SHAP and ALE-Based XAI Approach on the BIST Sustainability Index

Demet Ever & Ahmet Çankal

Indonesian Journal of Sustainability Accounting and Management2025https://doi.org/10.20448/ijsam.v9i2.7942article
ABDC C
Weight
0.50

What the paper says

The primary objective of this study is to examine the relationship between carbon emissions and firm profitability using Explainable Artificial Intelligence (XAI) methods. The research analyzes various machine learning (ML) techniques to predict firm profitability. Additionally, XAI methods such as Shapley Additive Explanations (SHAP) and Accumulated Local Effects (ALE) are employed to enhance interpretability for decision-makers. The study focuses on firms listed in the Borsa Istanbul Sustainability Index (XUSRD), utilizing 189 firm-year data points collected from sustainability, operational, and integrated reports between 2021 and 2023. The findings indicate that low carbon emissions positively influence Return on Assets (ROA), while high emissions have mixed effects, positive in some firms and negative in others. Regarding Return on Equity (ROE), the analysis reveals a negative trend. Furthermore, Earnings Per Share (EPS) emerged as the variable with the highest contribution to both profitability models. The Random Forest algorithm was identified as the most effective method for predicting both ROA and ROE. This study contributes to the emerging literature by applying XAI techniques, specifically SHAP and ALE, to interpret machine learning-based profitability models within the context of carbon accounting, offering valuable insights for stakeholders and policymakers.

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https://doi.org/https://doi.org/10.20448/ijsam.v9i2.7942

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@article{demet2025,
  title        = {{Carbon Emissions and Firm Profitability: A SHAP and ALE-Based XAI Approach on the BIST Sustainability Index}},
  author       = {Demet Ever & Ahmet Çankal},
  journal      = {Indonesian Journal of Sustainability Accounting and Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.20448/ijsam.v9i2.7942},
}

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Carbon Emissions and Firm Profitability: A SHAP and ALE-Based XAI Approach on the BIST Sustainability Index

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.