Environmental, Social, and Governance Investment Decisions Among Students: Partial Least Squares and Machine Learning Analysis - Bill Pangayow; Juliana Waromi; Cornelia Matani; Yubelina Mamoribo (Studi Akuntansi, Keuangan, dan Manajemen, 2026)
Purpose: This study aims to explore the factors influencing university students' interest in investing in companies that prioritize Environmental, Social, and Governance (ESG) principles in Indonesia, focusing on financial literacy, ESG awareness, subjective norms, and ESG risk perceptions. Methodology: A quantitative approach was employed using survey data collected from 104 accounting students at two public universities. The analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) and machine learning-based PLS regression, providing both causal inference and predictive modeling. Results: The study found that ESG awareness and subjective norms were the strongest predictors of students' interest in ESG investments. Financial literacy and ESG risk perception had weaker influences. PLS-SEM yielded an R² of 0.653, while PLS the regression showed an average R² of 0.482. Conclusions: ESG awareness and subjective norms are critical in shaping students' investment behavior, with ESG education in curricula and leveraging social influence being crucial to This promotes sustainable investment decisions. Financial literacy alone did not significantly affect ESG investment interest. Limitations: The study is limited by its sample size, which only includes students from two universities, and its cross-sectional design, restricting generalizability and the examination of changes over time. Contributions: This research provides a novel framework for understanding ESG investment behavior by integrating PLS-SEM and machine learning-based PLS regression, contributing to both theoretical insights and practical implications for promoting sustainable investment practices.