Table 1 Prior studies on ESG assessment... | Emerald Publishing

Table 1

Prior studies on ESG assessment and reporting

Study	Domain/Data	Methodology	Key findings	Limitations/Relevance to this study
Boiral (2009)	Corporate reports (mining sector)	Manual content analysis	Revealed selective emphasis and greenwashing in disclosures	Small sample: qualitative bias, shows need for scalable text analytics
Baldini et al. (2018)	Cross-industry firms	Panel regression on GRI adoption	Institutional pressures drive ESG disclosure	Quantitative but no textual depth
Maibaum et al. (2024)	Corporate ESG reports	Comparative text-mining tool evaluation	Tool choice alters classification accuracy and interpretability	Highlights the importance of methodological transparency for DSS design
Lee et al. (2025)	Cross-sector ESG data	NLP model (ESG-KIBERT)	Improved classification using domain lexicons	Focuses on scoring; no discourse context
Abdel-Tawab et al. (2023)	Construction projects	Case study on BIM implementation	BIM improves environmental sustainability tracking	Technological focus; lacks linguistic analysis
Gałecka-Drozda et al. (2021)	Corporate ESG reports	Content and sentiment analysis	Detected greenwashing patterns	External disclosure only
Qi et al. (2023)	Infrastructure projects	Mixed methods case study	Identified implementation barriers to ESG integration	Lacks computational text analysis
Roufosse et al. (2024)	Corporate texts	Knowledge-aware transformer model	Enhanced ESG classification accuracy	Predictive orientation: ignores framing effects

Study	Domain/Data	Methodology	Key findings	Limitations/Relevance to this study
Boiral (2009)	Corporate reports (mining sector)	Manual content analysis	Revealed selective emphasis and greenwashing in disclosures	Small sample: qualitative bias, shows need for scalable text analytics
Baldini et al. (2018)	Cross-industry firms	Panel regression on GRI adoption	Institutional pressures drive ESG disclosure	Quantitative but no textual depth
Maibaum et al. (2024)	Corporate ESG reports	Comparative text-mining tool evaluation	Tool choice alters classification accuracy and interpretability	Highlights the importance of methodological transparency for DSS design
Lee et al. (2025)	Cross-sector ESG data	NLP model (ESG-KIBERT)	Improved classification using domain lexicons	Focuses on scoring; no discourse context
Abdel-Tawab et al. (2023)	Construction projects	Case study on BIM implementation	BIM improves environmental sustainability tracking	Technological focus; lacks linguistic analysis
Gałecka-Drozda et al. (2021)	Corporate ESG reports	Content and sentiment analysis	Detected greenwashing patterns	External disclosure only
Qi et al. (2023)	Infrastructure projects	Mixed methods case study	Identified implementation barriers to ESG integration	Lacks computational text analysis
Roufosse et al. (2024)	Corporate texts	Knowledge-aware transformer model	Enhanced ESG classification accuracy	Predictive orientation: ignores framing effects