ESG Content Intensity and Sustainability Report Timeliness

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Authors: Abdullah Kürşat Merter, Beylem Çelik, GÖKHAN ÖZER
Cited by: 3

Abstract

This study investigates the relationship between ESG content intensity and disclosure speed while analyzing the moderating role of board-level sustainability committees. The study employs a quantitative research design using a panel dataset of non-financial firms listed on the BIST Sustainability Index from 2014 to 2023. ESG content intensity is measured using BERT-based computational text analysis, and hypotheses are tested using fixed-effects panel regression models. Higher ESG content intensity has been demonstrated to be significantly associated with accelerated report disclosure. The role of sustainability committees in promoting efficiency in reporting processes is also a salient factor. However, a substantial negative interaction effect indicates that committee effectiveness diminishes as content complexity increases, thereby demonstrating a governance bottleneck. For regulators, the findings suggest that uniform disclosure deadlines may be counterproductive; tiered deadlines based on content complexity could be more effective. For practitioners, the results highlight the need to invest in digital reporting infrastructure to mitigate governance bottlenecks. For investors, disclosure timeliness can serve as a quantifiable metric of managerial agility and information risk, with delays in committee-led firms signaling potential internal control weaknesses. This study provides the first systematic examination of the ESG content-timeliness relationship in an emerging market using advanced NLP techniques. It introduces "temporal signaling" to sustainability literature and offers novel empirical evidence on the dual role of sustainability committees, providing a more nuanced understanding of corporate disclosure dynamics.

Fields of Study & Subjects

Corporate Social Responsibility Reporting Auditing Earnings Management Governance Impact of AI and Big Data on Business and Society

Publication details

Journal / source
Journal of Intelligent Decision Making and Granular Computing
Publisher
Scientific Oasis
Volume
2
Issue
1
Pages
76–99
Publication date
18 March 2026