An Integrated CRITIC–Weighted Fuzzy Soft Set Framework for Sustainable Stock Investment Decision-Making in Indonesia

Environmentally friendly (green) stock investment has evolved into a global trend over the past few decades, including in the Indonesian capital market. However, the process of selecting sustainability-oriented stocks involves various complex criteria that are often qualitative, subjective, and uncertain. Therefore, an analytical tool is needed to support the decision-making process more adaptively and objectively. This study proposes the Criteria Importance Through Inter-criteria Correlation–Weighted Fuzzy Soft Set (CRITIC-WFSS) integration model, a decision-making method that combines WFSS with the objective, data-driven weighting mechanism of the CRITIC method. In the proposed model, parameter weights are determined by considering data variation (standard deviation) and inter-criteria correlation, ensuring that more discriminative and informative parameters receive higher weights. The model was applied to data on environmentally friendly stocks in the SRI-KEHATI Index, obtained from the Indonesia Stock Exchange (IDX) official website, to evaluate and identify stocks with optimal performance. The model’s performance is evaluated through a comparative study with the AHP-WFSS and Entropy–WFSS methods, complemented by a sensitivity analysis. The results show that UNVR ranked highest with a perfect score of 1, indicating an optimal balance between financial performance and sustainability. Furthermore, a comparative study demonstrated that CRITIC-WFSS can generate rankings that are more reliable, appropriate, and logical than those generated by two comparison methods. Meanwhile, the results of the sensitivity analysis indicate that the CRITIC-WFSS model demonstrates strong robustness to variations in input parameters, ensuring stable rankings. The model shows significant potential to support more accurate and transparent investment decision-making by generating consistent stock rankings based on a balanced integration of financial, and sustainability (environmental, social, and governance (ESG)) aspects. This research was conducted in order to support the achievement of various goals through SDG 8 (Decent Work and Economic Growth).

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Publication Details

Journal
Mathematics
Published
2025-12-11
DOI
https://doi.org/10.3390/math13243952
Primary Topic
Energy and Environmental Sustainability
Type
article
Field-Weighted Citation Impact
0.00

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article

An Integrated CRITIC–Weighted Fuzzy Soft Set Framework for Sustainable Stock Investment Decision-Making in Indonesia

Ema Carnia, Sukono Sukono, Mugi Lestari
Mathematics
Energy and Environmental Sustainability
article

An Integrated CRITIC–Weighted Fuzzy Soft Set Framework for Sustainable Stock Investment Decision-Making in Indonesia

Ema Carnia, Sukono Sukono, Mugi Lestari
article en

Abstract

Environmentally friendly (green) stock investment has evolved into a global trend over the past few decades, including in the Indonesian capital market. However, the process of selecting sustainability-oriented stocks involves various complex criteria that are often qualitative, subjective, and uncertain. Therefore, an analytical tool is needed to support the decision-making process more adaptively and objectively. This study proposes the Criteria Importance Through Inter-criteria Correlation–Weighted Fuzzy Soft Set (CRITIC-WFSS) integration model, a decision-making method that combines WFSS with the objective, data-driven weighting mechanism of the CRITIC method. In the proposed model, parameter weights are determined by considering data variation (standard deviation) and inter-criteria correlation, ensuring that more discriminative and informative parameters receive higher weights. The model was applied to data on environmentally friendly stocks in the SRI-KEHATI Index, obtained from the Indonesia Stock Exchange (IDX) official website, to evaluate and identify stocks with optimal performance. The model’s performance is evaluated through a comparative study with the AHP-WFSS and Entropy–WFSS methods, complemented by a sensitivity analysis. The results show that UNVR ranked highest with a perfect score of 1, indicating an optimal balance between financial performance and sustainability. Furthermore, a comparative study demonstrated that CRITIC-WFSS can generate rankings that are more reliable, appropriate, and logical than those generated by two comparison methods. Meanwhile, the results of the sensitivity analysis indicate that the CRITIC-WFSS model demonstrates strong robustness to variations in input parameters, ensuring stable rankings. The model shows significant potential to support more accurate and transparent investment decision-making by generating consistent stock rankings based on a balanced integration of financial, and sustainability (environmental, social, and governance (ESG)) aspects. This research was conducted in order to support the achievement of various goals through SDG 8 (Decent Work and Economic Growth).

MathematicsVol. 13(24)
Padjadjaran University (ID)
Ministrstvo za visoko šolstvo, znanost in tehnologijo, Lembaga Pengelola Dana Pendidikan, Universitas Padjadjaran
Openalex Percentile: Top 71%
Energy and Environmental Sustainability
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