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A Hybrid Multi-Criteria Decision-Making Model for Evaluating Companies’ Green Credit Rating

Author

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  • Chia-Chen Yang

    (Department of Finance, Ling Tung University, Taichung 40852, Taiwan
    These authors contributed equally to this work.)

  • Shang-Ling Ou

    (Department of Agronomy, National Chung Hsing University, Taichung 40227, Taiwan
    These authors contributed equally to this work.)

  • Li-Chang Hsu

    (Department of Finance, Ling Tung University, Taichung 40852, Taiwan)

Abstract

Along with economic development and social progress, environmental issues are increasingly becoming the subject of public concern. Through green credit, banks intentionally direct money into resource-conserving technology development and environmental protection industries, thus, encouraging enterprises to focus on green products. Therefore, establishing a reasonable green credit evaluation mechanism for banks is an important issue. Based on this, this study combines grey relational analysis (GRA), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), analytic network process (ANP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a hybrid multi-criteria decision-making (MCDM) model for quantifying data and, thereby, to establish a green credit rating mechanism. In order to verify the model, this study combines credit risk and economic, environmental and social performance evaluation criteria as green credit evaluation criteria. There are 55 high-tech listed companies in Taiwan in 2014 taken as the evaluation objects and conducted for a performance ranking. The empirical results can serve as a reference for financial authorities promoting green finance policies and for investors making investment decisions.

Suggested Citation

  • Chia-Chen Yang & Shang-Ling Ou & Li-Chang Hsu, 2019. "A Hybrid Multi-Criteria Decision-Making Model for Evaluating Companies’ Green Credit Rating," Sustainability, MDPI, vol. 11(6), pages 1-23, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1506-:d:213339
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    References listed on IDEAS

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    2. Pranith Kumar Roy & Krishnendu Shaw, 2021. "A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    3. Chunling Li & Khansa Pervaiz & Muhammad Asif Khan & Faheem Ur Rehman & Judit Oláh, 2019. "On the Asymmetries of Sovereign Credit Rating Announcements and Financial Market Development in the European Region," Sustainability, MDPI, vol. 11(23), pages 1-14, November.
    4. Qicheng Zhao & Zhouwei Wang & Yuping Song, 2024. "Systematic Research on Multi-dimensional and Multiple Correlation Contagion Networks of Extreme Risk in China’s Banking Industry," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1137-1162, August.
    5. N. Denuwara & A. Kim & V. Atree & P. Newenhisen & C. Gibson & D. Schork & M. Hakovirta, 2022. "Corporate economic performance and sustainability indices: a study based on the Dow Jones Sustainability Index," SN Business & Economics, Springer, vol. 2(7), pages 1-22, July.
    6. Vogl, Markus & Kojić, Milena & Mitić, Petar, 2024. "Dynamics of green and conventional bond markets: Evidence from the generalized chaos analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    7. Marco Locurcio & Francesco Tajani & Pierluigi Morano & Debora Anelli & Benedetto Manganelli, 2021. "Credit Risk Management of Property Investments through Multi-Criteria Indicators," Risks, MDPI, vol. 9(6), pages 1-23, June.
    8. Chun-Ho Chen, 2019. "A New Multi-Criteria Assessment Model Combining GRA Techniques with Intuitionistic Fuzzy Entropy-Based TOPSIS Method for Sustainable Building Materials Supplier Selection," Sustainability, MDPI, vol. 11(8), pages 1-18, April.

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