How can we improve entrepreneurial dynamics in electric vehicle manufacturing for a sustainable future: insights using a deep learning-based hybrid PLS-SEM-ANN approach

This study examines entrepreneurial dynamics in the electric vehicle (EV) sector, focusing on motivations, personality traits, and external influences such as government policies, innovation, and competition. The study developed a research model based on the creation and discovery theory. The proposed model was evaluated with data obtained from 389 participants through a deep learning-based artificial neural network (ANN) and the partial least squares structural equation modeling (PLS-SEM) approach. The research identifies key predictors of entrepreneurial behavior, including innovativeness, technological advancement, and entrepreneurial personality traits, which significantly impact motivation and enthusiasm for EV ventures. The findings underscore the crucial role of government policies in fostering entrepreneurial enthusiasm while competitive pressures and innovation drive the development of strong business attributes. Entrepreneurial motivation emerges as a critical mediator, bridging various predictors and enthusiasm for EV adoption. By integrating discovery and creation theories, this research offers a comprehensive theoretical framework, providing actionable insights for policymakers and industry stakeholders to promote sustainable entrepreneurship. Despite limitations related to generalizability and the study’s cross-sectional nature, the findings lay a robust foundation for future research on entrepreneurial ecosystems in emerging industries. This study advances the understanding of entrepreneurial dynamics in the EV sector and highlights pathways for fostering innovation and sustainability in entrepreneurship.