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The Quest for an ESG Country Rank: A Performance Contribution Analysis/MCDM Approach

Author

Listed:
  • Yong Tan

    (School of Management, University of Bradford, Bradford BD7 1DP, UK)

  • Amir Karbassi Yazdi

    (Departamento de Ingeniería Industrial y de Sistemas, Facultad de Ingeniería, Universidad de Tarapacá, Arica 1000000, Chile)

  • Jorge Antunes

    (COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme 355, Rio de Janeiro 21949-900, Brazil)

  • Peter Wanke

    (COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme 355, Rio de Janeiro 21949-900, Brazil)

  • Angappa Gunasekaran

    (School of Business Administration, Penn State, Harrisburg, PA 16801, USA)

  • Henrique Luiz Corrêa

    (Crummer Graduate School of Business, Rollins College, Winter Park, FL 32789, USA)

  • Giuliani Coluccio

    (Departamento de Ingeniería Industrial y de Sistemas, Facultad de Ingeniería, Universidad de Tarapacá, Arica 1000000, Chile)

Abstract

Utilizing Multi-Criteria Decision Analysis (MCDA) methods based on environmental, social, and governance (ESG) factors to rank countries according to these criteria aims to evaluate and prioritize countries based on their performance in environmental, social, and governance aspects. The contemporary world is influenced by a multitude of factors, which consequently impact our lives. Various models are devised to assess company performance, with the intention of enhancing quality of life. An exemplary case is the ESG framework, encompassing environmental, social, and governmental dimensions. Implementing this framework is intricate, and many nations are keen on understanding their global ranking and avenues for enhancement. Different statistical and mathematical methods have been employed to represent these rankings. This research endeavors to examine both types of methods to ascertain the one yielding the optimal outcome. The ESG model comprises eleven factors, each contributing to its efficacy. We employ the Performance Contribution Analysis (PCA), Clifford algebra method, and entropy weight technique to rank these factors, aiming to identify the most influential factor in countries’ ESG-based rankings. Based on prioritization results, political stability (PSAV) and the voice of accountability (VA) emerge as pivotal elements. In light of the ESG model and MCDA methods, the following countries exhibit significant societal impact: Sweden, Finland, New Zealand, Luxembourg, Switzerland, Denmark, India, Norway, Canada, Germany, Austria, and Australia. This research contributes in two distinct dimensions, considering the global context and MCDA methods employed. Undoubtedly, a research gap is identified, necessitating the development of a novel model for the comparative evaluation of countries in relation to prior studies.

Suggested Citation

  • Yong Tan & Amir Karbassi Yazdi & Jorge Antunes & Peter Wanke & Angappa Gunasekaran & Henrique Luiz Corrêa & Giuliani Coluccio, 2024. "The Quest for an ESG Country Rank: A Performance Contribution Analysis/MCDM Approach," Mathematics, MDPI, vol. 12(12), pages 1-24, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:12:p:1865-:d:1415272
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    References listed on IDEAS

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    1. J. V. Zidek & W. Sun & N. D. Le, 2000. "Designing and integrating composite networks for monitoring multivariate gaussian pollution fields," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(1), pages 63-79.
    2. Carolina Almeida Cruz & Florinda Matos, 2023. "ESG Maturity: A Software Framework for the Challenges of ESG Data in Investment," Sustainability, MDPI, vol. 15(3), pages 1-18, February.
    3. Panos Xidonas & Eric Essner, 2024. "On ESG Portfolio Construction: A Multi-Objective Optimization Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 21-45, January.
    4. Jiahui Su & Yidi Sun, 2023. "An Improved TOPSIS Model Based on Cumulative Prospect Theory: Application to ESG Performance Evaluation of State-Owned Mining Enterprises," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    5. F. Alkaraan & K. Albitar & K. Hussainey & V.G. Venkatesh, 2022. "Corporate Transformation toward Industry 4.0 and Financial Performance: The Influence of Environmental, Social, and Governance (ESG)," Post-Print hal-04445029, HAL.
    6. Teng, Sin Yong & How, Bing Shen & Leong, Wei Dong & Teoh, Jun Hao & Cheah, Adrian Chee Siang & Motavasel, Zahra & Lam, Hon Loong, 2019. "Principal component analysis-aided statistical process optimisation (PASPO) for process improvement in industrial refineries," MPRA Paper 94058, University Library of Munich, Germany, revised 01 Jan 2019.
    7. Xiaokai Meng & Ghulam Muhammad Shaikh, 2023. "Evaluating Environmental, Social, and Governance Criteria and Green Finance Investment Strategies Using Fuzzy AHP and Fuzzy WASPAS," Sustainability, MDPI, vol. 15(8), pages 1-19, April.
    8. Alkaraan, Fadi & Albitar, Khaldoon & Hussainey, Khaled & Venkatesh, VG, 2022. "Corporate transformation toward Industry 4.0 and financial performance: The influence of environmental, social, and governance (ESG)," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    9. Chithambaranathan, P. & Subramanian, Nachiappan & Gunasekaran, Angappa & Palaniappan, PL.K., 2015. "Service supply chain environmental performance evaluation using grey based hybrid MCDM approach," International Journal of Production Economics, Elsevier, vol. 166(C), pages 163-176.
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