The role of data analytics in enhancing ESG transparency in the corporate sector of Bangladesh
Department of Economics and Business Analytics, University of New Haven, USA.
Research Article
Global Journal of Engineering and Technology Advances, 2025, 22(01), 081-093.
Article DOI: 10.30574/gjeta.2025.22.1.0245
Publication history:
Received on 22 November 2024; revised on 16 January 2025; accepted on 19 January 2025
Abstract:
This study explores the role of data analytics in enhancing the transparency, accountability, and reliability of Environmental, Social, and Governance (ESG) reporting within the corporate sector. As global demand for more accurate and standardized ESG disclosures increases, organizations are turning to advanced data analytics tools, such as artificial intelligence (AI), machine learning, and blockchain, to improve the quality and verifiability of their ESG reports. This research employs a mixed-methods approach, combining a survey of corporate sustainability officers, in-depth interviews with industry experts, and case studies of companies utilizing data analytics in their ESG reporting. The findings reveal that while larger corporations have successfully integrated data analytics into their ESG practices, small and medium-sized enterprises (SMEs) face significant barriers, including resource constraints, data quality issues, and lack of standardized ESG metrics. The study also identifies the key benefits of data analytics, including improved transparency, better risk management, and enhanced regulatory compliance. Despite challenges, the adoption of data analytics in ESG reporting is shown to increase stakeholder trust and offer a competitive advantage. The study concludes with recommendations for companies to invest in data quality, build technical capacity, and leverage emerging technologies to meet growing regulatory requirements and improve their ESG performance.
Keywords:
Data Analytics; ESG Reporting; Corporate Sustainability; Transparency; Accountability; Artificial Intelligence; Machine Learning; Blockchain; Regulatory Compliance; Small and Medium-sized Enterprises (SMEs)
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Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0