This study thoroughly examines the relationship between environmental, social and governance (ESG) scores and their subcategories with the investment decisions made by foreign institutional investors (FII). These subcategories include resource use, emission reduction and innovation under the environmental pillar, workforce, human rights, community and product responsibility under the social pillar and management, shareholders and CSR strategy under the governance pillar.
A machine learning technique known as “topic modeling” is used to analyse the current literature on ESG. To investigate the correlation between ESG scores and their subcategories with the investment decisions made by FII and to address concerns regarding multicollinearity and overfitting, a penalty-based regression model is employed.
The findings indicate that FIIs invest in firms with higher emission reduction and innovation scores under the environmental indicator. Additionally, firms with high human rights, community and product responsibility scores under the social indicator category have a positive relationship with FII investors. All subcategories of governance indicators, such as corporate social responsibility (CSR), strategy, shareholders and management scores, also positively impact FII investment. Of the three indicators, i.e. ESG, non-promoter FIIs give maximum weightage to governance indicators.
Since ESG is a contemporary topic, the findings on the relationship between different categories of ESG on FII investment will support managers in their FII investment. Also, the study will help the government frame policy decisions on ESG.
Previous studies have explored the impact of the overall ESG indicators on FII investments, but they have not specifically studied the influence of sub-indicators within these categories on investment decisions. By addressing this gap, the study enhances stakeholder theory by identifying and prioritizing the various subcategories of ESG indicators that impact FII investment decisions.
