Year: 2024 | Month: December | Volume 12 | Issue 2
Beyond the Balance Sheet: Synergizing Financial Sustainability
and Information Disclosure Index with ESG Performance Metrics
in Indian Corporations
Ashutosh Parhi
Parle Kalyan Chakravarthy
Kalee Prasanna Pattanayak
Rabi Narayan Subudhi
DOI:10.30954/2322-0465.2.2024.8
Abstract:
This research article examines the impact of the Financial Sustainability and Information Disclosure Index (FSIDI) on firms’ Environmental, Social, and Governance (ESG) performance dimensions. By analysing the relationship between financial transparency and ESG outcomes, the study seeks to determine how disclosure practices influence corporate sustainability strategies. The study uses panel data from NSE-listed companies over the period 2016 to 2023. It employs Fixed Effects (FE) and Random Effects (RE) models, along with heteroskedasticity tests and the Hausman test to select the appropriate model specification for analysing the data. The results indicate a significant positive effect of FSIDI on Environmental and Social Performance, suggesting that financial transparency plays a vital role in enhancing these areas. However, FSIDI’s influence on Governance Performance and overall Sustainability Performance is statistically in significant. The findings offer practical insights for corporate managers, emphasizing the importance of improving financial disclosure practices to enhance Environmental and Social Performance. However, firms should consider other governance factors to boost overall sustainability efforts. Future research is
encouraged to explore additional contextual variables and alternative approaches to better understand the relationship between financial transparency and ESG dimensions. This research offers a novel contribution by examining the impact of the Financial Sustainability and Information Disclosure Index (FSIDI) on distinct Environmental, Social, and Governance (ESG) dimensions. Unlike previous studies, it employs a robust methodological framework with both Fixed Effects (FE) and Random Effects (RE) models, to ensure reliable results.
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