Assessing the alignment of corporate ESG disclosures with the UN sustainable development goals: a BERT-based text analysis

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Podrobná bibliografie
Vydáno v:	Data Technologies and Applications vol. 59, no. 1 (2025), p. 19-40
Hlavní autor:	Kim, Hyogon
Další autoři:	Lee, Eunmi, Yoo, Donghee
Vydáno:	Emerald Group Publishing Limited
Témata:	Samsung Electronics Co Ltd United States > US Form 10-K Data processing Trends Data mining International organizations Environmental impact Keywords Investors Social responsibility Neural networks Public companies Sustainable development Text analysis Decision making Impact analysis Sentences Environmental social & governance Disclosure Models Companies Sustainability COVID-19 Classifiers Global perspective Interlocking directorates Business Textual analysis Pandemics Investments Language modeling Literature Reviews World Problems Predominantly White Institutions Influence of Technology Sex Fairness Developed Nations Language Processing
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Popis
Abstrakt:	PurposeThis study aims to provide measurable information that evaluates a company’s ESG performance based on the conceptual connection between ESG, non-financial elements of a company and the UN Sustainable Development Goals (SDGs) for resolving global issues.Design/methodology/approachA novel data processing method based on the BERT is presented and applied to analyze the changes and characteristics of SDG-related ESG texts from companies’ disclosures over the past decade. Specifically, ESG-related sentences are extracted from 93,277 Form 10-K filings disclosed between 2010 and 2022 and the similarity between these extracted sentences and SDGs statements is calculated through sentence transformers. A classifier is created by fine-tuning FinBERT, a financial domain-specific pre-trained language model, to classify the sentences into eight ESG classes.FindingsThe quantified results obtained from the classifier reveal several implications. First, it is observed that the trend of SDG-related ESG sentences shows a slow and steady increase over the past decade. Second, large-cap companies relatively have a greater amount of SDG-related ESG disclosures than small-cap companies. Third, significant events such as the COVID-19 pandemic greatly impact the changes in disclosure content.Originality/valueThis study presents a novel approach to textual analysis using neural network-based language models such as BERT. The results of this study provide meaningful information and insights for investors in socially responsible investment and sustainable investment and suggest that corporations need a long-term plan regarding ESG disclosures.
ISSN:	2514-9288 2514-9318 0033-0337 1758-7301
DOI:	10.1108/DTA-01-2024-0065
Zdroj:	ABI/INFORM Global