The Role of Machine Learning in Cultivating Green Entrepreneurs: A Study of Governance in South Indian Educational Institutes

The transition to a sustainable economy is imperative in the face of global environmental challenges. A pivotal element in this transformation is the cultivation of green entrepreneurship. This study investigates the role of governance in various educational institutions across South India in nurturing the entrepreneurial intentions of students towards establishing green ventures. By employing machine learning techniques on survey data, we aim to detract from the inclination to pursue green entrepreneurship. Despite the burgeoning need for sustainable business practices, there is a gap in understanding how institutional governance affects the propensity of students to embark on green entrepreneurial endeavors. This study addresses the gap by examining the drivers and deterrents within the educational ecosystems that influence students' entrepreneurial ambitions. To address the research problem, we utilized a data-driven approach, applying several machine learning models to predict the likelihood of entrepreneurial intentions among students. This predictive analysis helps in identifying the key institutional factors that could foster and hinder green entrepreneurial activities. Our methodology encompasses quantitative analysis of survey data collected from students across various institutions. The data underwent preprocessing, feature selection, and was subjected to machine learning models for classification. The analysis involved comparing the predictive power of Logistic Regression, Decision Trees, Random Forests, and SVMs. The findings indicate that certain governance practices within educational institutions significantly influence students' green entrepreneurial intentions. The Random Forest model, in particular, demonstrated high accuracy and provided deep insights into the influential factors driving these intentions.