IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i24p16872-d1300739.html
   My bibliography  Save this article

esg2go: A Method to Reduce Bias, Improve Coherence, and Increase Practicality of ESG Rating and Reporting

Author

Listed:
  • Isa Cakir

    (Center for Corporate Responsibility and Sustainability (CCRS), School of Management Fribourg (HEG-FR), 1700 Fribourg, Switzerland)

  • Philipp Aerni

    (Center for Corporate Responsibility and Sustainability (CCRS), School of Management Fribourg (HEG-FR), 1700 Fribourg, Switzerland
    School of Management Fribourg, Western University of Applied Sciences (HES-SO), Chemin du Musée 4, 1700 Fribourg, Switzerland
    Science and Public Policy Unit, Department of Plant Microbial Biology (IPMB), University of Zurich, 8032 Zurich, Switzerland)

  • Manfred Max Bergman

    (Department of Social Sciences, University of Basel, 4501 Basel, Switzerland
    Family Medicine, University of Michigan, Ann Arbor, MI 48109, USA)

  • Benjamin Cakir

    (Center for Corporate Responsibility and Sustainability (CCRS), School of Management Fribourg (HEG-FR), 1700 Fribourg, Switzerland)

Abstract

Rating agencies that assess a company’s environmental, social, and corporate governance (ESG) impact have been subject to public and academic scrutiny due to divergent and often biased rating outcomes. Concurrently, an evolving regulatory environment mandates publicly listed companies to report on ESG and climate emissions, taking into account supply chain risks as well. As a result, small and medium-sized enterprises (SMEs) are increasingly asked as suppliers to present a credible sustainability certificate. The esg2go rating and reporting system aims at improving the credibility and practicality of corporate sustainability assessment. It was jointly developed with its users and relevant stakeholders and is based on a calibrated benchmarking system from verifiable data. The rating method enables the measurement and comparison of sector- and firm size-specific sustainability performance. Its underlying adaptive parametrization is derived from a coherent and pragmatic definition of SME sustainability as the ‘ability to co-exist’. Our data analyses indicate that our scoring function is able to minimize bias and deliver a fair comparability between SMEs. We conclude that esg2go represents a pragmatic and innovative approach to enhance the fairness and accuracy of corporate sustainability assessment.

Suggested Citation

  • Isa Cakir & Philipp Aerni & Manfred Max Bergman & Benjamin Cakir, 2023. "esg2go: A Method to Reduce Bias, Improve Coherence, and Increase Practicality of ESG Rating and Reporting," Sustainability, MDPI, vol. 15(24), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16872-:d:1300739
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/24/16872/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/24/16872/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Samuel Drempetic & Christian Klein & Bernhard Zwergel, 2020. "The Influence of Firm Size on the ESG Score: Corporate Sustainability Ratings Under Review," Journal of Business Ethics, Springer, vol. 167(2), pages 333-360, November.
    2. Paul Griffin & Amy Myers Jaffe, 2022. "Challenges for a climate risk disclosure mandate," Nature Energy, Nature, vol. 7(1), pages 2-4, January.
    3. Oliver Lukason & María-del-Mar Camacho-Miñano, 2021. "What Best Explains Reporting Delays? A SME Population Level Study of Different Factors," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    4. Shashwat Koirala, 2019. "SMEs: Key drivers of green and inclusive growth," OECD Green Growth Papers 2019/03, OECD Publishing.
    5. Aaron K. Chatterji & Rodolphe Durand & David I. Levine & Samuel Touboul, 2016. "Do ratings of firms converge? Implications for managers, investors and strategy researchers," Strategic Management Journal, Wiley Blackwell, vol. 37(8), pages 1597-1614, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Valeria D’Amato & Rita D’Ecclesia & Susanna Levantesi, 2021. "Fundamental ratios as predictors of ESG scores: a machine learning approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1087-1110, December.
    2. Bauckloh, Michael Tobias & Beyer, Victor & Klein, Christian, 2022. "Does it pay to invest in dirty industries? New insights on the shunned-stock hypothesis," CFR Working Papers 22-07, University of Cologne, Centre for Financial Research (CFR).
    3. Sofia Brito-Ramos & Maria Céu Cortez & Florinda Silva, 2022. "Do sustainability signals diverge? An analysis of labeling schemes for socially responsible investments ," Working Papers hal-04064367, HAL.
    4. Fiordelisi, Franco & Ricci, Ornella & Santilli, Gianluca, 2023. "Environmental engagement and stock price crash risk: Evidence from the European banking industry," International Review of Financial Analysis, Elsevier, vol. 88(C).
    5. Xiaoyan Xu & Hong Zhao, 2024. "An Empirical Study on ESG Evaluation of Chinese Energy Enterprises Based on High-Quality Development Goals—A Case Study of Listed Company Data," Sustainability, MDPI, vol. 16(15), pages 1-22, August.
    6. Louis Maximilian Ronalter & Merce Bernardo & Javier Manuel Romaní, 2023. "Quality and environmental management systems as business tools to enhance ESG performance: a cross-regional empirical study," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9067-9109, September.
    7. Valeria D’Amato & Rita D’Ecclesia & Susanna Levantesi, 2022. "ESG score prediction through random forest algorithm," Computational Management Science, Springer, vol. 19(2), pages 347-373, June.
    8. Deli Wang & Ke Peng & Kaiye Tang & Yewei Wu, 2022. "Does Fintech Development Enhance Corporate ESG Performance? Evidence from an Emerging Market," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    9. Zhao, Yuanshuang & Dong, Liang & Sun, Yuhang & Ma, Yunning & Zhang, Ning, 2024. "Is air pollution the original sin of firms? The impact of air pollution on firms' ESG scores," Energy Economics, Elsevier, vol. 136(C).
    10. Caterina Lucarelli & Sabrina Severini, 2024. "Anatomy of the chimera: Environmental, Social, and Governance ratings beyond the myth," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4198-4217, July.
    11. Ilze Zumente & Nataļja Lāce, 2021. "ESG Rating—Necessity for the Investor or the Company?," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    12. Ting-Ting Li & Kai Wang & Toshiyuki Sueyoshi & Derek D. Wang, 2021. "ESG: Research Progress and Future Prospects," Sustainability, MDPI, vol. 13(21), pages 1-28, October.
    13. Tobias Bauckloh & Stefan Schaltegger & Sebastian Utz & Sebastian Zeile & Bernhard Zwergel, 2023. "Active First Movers vs. Late Free-Riders? An Empirical Analysis of UN PRI Signatories’ Commitment," Journal of Business Ethics, Springer, vol. 182(3), pages 747-781, January.
    14. Dumrose, Maurice & Rink, Sebastian & Eckert, Julia, 2022. "Disaggregating confusion? The EU Taxonomy and its relation to ESG rating," Finance Research Letters, Elsevier, vol. 48(C).
    15. Schoonjans, Eline, 2024. "From diversity to sustainability: Environmental and social spillover effects of board gender quotas," Journal of Economic Behavior & Organization, Elsevier, vol. 222(C), pages 314-331.
    16. Charl de Villiers & Jing Jia & Zhongtian Li, 2022. "Corporate social responsibility: A review of empirical research using Thomson Reuters Asset4 data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(4), pages 4523-4568, December.
    17. Staněk Gyönyör, Lucie & Horváth, Matúš, 2024. "Does ESG affect stock market dependence? An empirical exploration of S&P 1200 companies shows the divergent nature of E–S–G pillars," Research in International Business and Finance, Elsevier, vol. 69(C).
    18. Jian Zhou & Xiaodong Lei & Jianglong Yu, 2024. "ESG rating divergence and corporate green innovation," Business Strategy and the Environment, Wiley Blackwell, vol. 33(4), pages 2911-2930, May.
    19. Andre Höck & Tobias Bauckloh & Maurice Dumrose & Christian Klein, 2023. "ESG criteria and the credit risk of corporate bond portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 24(7), pages 572-580, December.
    20. Zhie Wang & Xiaoyong Wang & Xuexin Liu & Jun Zhang & Jingde Xu & Jun Ma, 2024. "A Novel Stacked Generalization Ensemble-Based Hybrid SGM-BRR Model for ESG Score Prediction," Sustainability, MDPI, vol. 16(16), pages 1-25, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16872-:d:1300739. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.