Factors Influencing University Students' Green Entrepreneurial Intention An Integrated Framework of UTAUT and VBN Theory

Abstract

With the rapid development of artificial intelligence (AI) technologies, their potential in green entrepreneurship has become increasingly evident, particularly in achieving sustainable development goals. Although AI can support green entrepreneurship by optimizing resource management, reducing energy consumption, and lowering emissions, its adoption faces numerous challenges. This paper aims to explore the application of AI in green entrepreneurship, focusing on the factors influencing the formation of Green Entrepreneurial Intention (GEI). By integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Value-Belief-Norm (VBN) theory, we construct an integrated framework to examine how performance expectancy, effort expectancy, social influence, facilitating conditions, and pro-environmental personal norms collectively influence entrepreneurs' decisions to adopt AI. Using survey data from 260 green entrepreneurs in Beijing, we applied Partial Least Squares Structural Equation Modeling (PLS-SEM) for analysis. The results show that all five factors significantly positively affect GEI, with pro-environmental personal norms having the strongest influence. This study offers a new theoretical perspective on green entrepreneurship and provides practical recommendations for policymakers, entrepreneurs, and AI technology providers in promoting the adoption of sustainable technologies.