Modelling ESG Investment Decisions of Retail Investors: A Logistic Regression Approach
摘要
As sustainable finance gains prominence, understanding the drivers of ESG investment adoption is critical for financial institutions and policymakers. Using Behavioral Reasoning Theory (BRT) as a conceptual framework, the paper clarifies how retail investors rationalize their decisions based on reasons for and against ESG investment. Employing binary logistic regression analysis, investors are categorized into ESG adopters, and non-adopters, allowing for a predictive analysis of key determinants influencing sustainable investment behavior. The SPSS 21software was used for the empirical analysis, and the findings reveal that higher financial literacy and trust in ESG ratings significantly increase the likelihood of ESG investment decision, while perceived risk and skepticism toward greenwashing serve as deterrents. This study provides empirical insights into the behavioral motivators and obstacles of ESG investment, hence expanding discussions on green finance and sustainable investment techniques. The results provide actionable recommendations for financial institutions, policymakers, and investors to enhance ESG transparency, investor education, and risk management strategies to drive sustainable investment growth.