Structural Equation Modeling of Dual Drivers: How Passion and Digital Economy Shape Academic Entrepreneurship in China's GBA

The integration of structural equation modeling (SEM) with a social science framework offers novel insights into academic entrepreneurship, particularly within high-growth digital ecosystems. A study was conducted to test a hypothesis using Partial Least Squares (PLS) techniques among 376 STEM academics in the Greater Bay Area (GBA) of China. The results of the study indicated that Entrepreneurial Passion (EP) and Digital Economy (DE) have a significant direct effect on Entrepreneurial Intentions (EI), while their interactions are insignificant. This finding challenges the traditional person-environment fit models. The present study employs municipal statistics data to operationalize digital economic indicators and utilizes a confirmatory factor analysis (CFA) to validate its conceptual framework. The study proposes that the institutionalized support system of the GBA regulates the entrepreneurial path and weakens the multiplier effect between individual enthusiasm and environmental factors. This study establishes a nexus between micro-level psychological frameworks and macro-level institutional theories, thereby furnishing policymakers with a dual-driver model to optimize strategies for the digital ecosystem.