The aim of this paper is to provide a ranking of companies, based on ESG scores, which accounts for the greenwashing phenomenon. LSEG publishes an index of controversies that measures the extent to which a company is exposed to scandals or legal disputes or fines. In order to account for the uncertainty arising from possible greenwashing, we propose the use of Triangular fuzzy numbers to model the ESG score adjusted for controversies. Fuzzy TOPSIS is used for the final ranking of companies. Results are benchmarked to the LSEG ranking adjusted for controversies and a standard TOPSIS ranking. By comparing the rankings obtained with the one developed by LSEG, significant differences emerge, attributable to the methodology used and data biases. The study highlights how both methods are effective tools for classifying corporate ESG performance, with fuzzy TOPSIS standing out for its innovation in addressing the limitations of traditional data.

Accounting for Controversies in ESG Scores: A Fuzzy TOPSIS Approach / Muzzioli, S., Capriotti, A., Vitale, L. (COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE). - In: Information Processing and Management of Uncertainty in Knowledge-Based Systems / [a cura di] Vantaggi, B., et al.. - [s.l], 2026. - ISBN 9783032289995. - pp. 90-103 [10.1007/978-3-032-29000-7_7]

Accounting for Controversies in ESG Scores: A Fuzzy TOPSIS Approach

Muzzioli, Silvia
;
Capriotti, Alessio;Vitale, Lorenzo
2026

Abstract

The aim of this paper is to provide a ranking of companies, based on ESG scores, which accounts for the greenwashing phenomenon. LSEG publishes an index of controversies that measures the extent to which a company is exposed to scandals or legal disputes or fines. In order to account for the uncertainty arising from possible greenwashing, we propose the use of Triangular fuzzy numbers to model the ESG score adjusted for controversies. Fuzzy TOPSIS is used for the final ranking of companies. Results are benchmarked to the LSEG ranking adjusted for controversies and a standard TOPSIS ranking. By comparing the rankings obtained with the one developed by LSEG, significant differences emerge, attributable to the methodology used and data biases. The study highlights how both methods are effective tools for classifying corporate ESG performance, with fuzzy TOPSIS standing out for its innovation in addressing the limitations of traditional data.
2026
Information Processing and Management of Uncertainty in Knowledge-Based Systems
Vantaggi, B., et al.
9783032289995
9783032290007
Accounting for Controversies in ESG Scores: A Fuzzy TOPSIS Approach / Muzzioli, S., Capriotti, A., Vitale, L. (COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE). - In: Information Processing and Management of Uncertainty in Knowledge-Based Systems / [a cura di] Vantaggi, B., et al.. - [s.l], 2026. - ISBN 9783032289995. - pp. 90-103 [10.1007/978-3-032-29000-7_7]
Muzzioli, Silvia; Capriotti, Alessio; Vitale, Lorenzo
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1411235
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex ND
social impact