Conference Agenda

Entrepreneurial intention is widely used as a central outcome in entrepreneurship education in engineering; however, less attention has been paid to how different predictors operate when ordered according to their proximity to entrepreneurial action under uncertainty. This study proposes and tests a layered activation model in which entrepreneurial intention is progressively explained through variables ranging from distal structural factors to proximal behavioral mechanisms. A questionnaire was administered to 497 third-year engineering students from three departments at a Chilean university. Measures included entrepreneurial intention, experimentation (as an effectuation-related behavior), cognitive flexibility-adaptability, polychronicity, openness, extraversion, demographic variables, work experience, and family entrepreneurship background. Hierarchical regression analyses revealed a progressive increase in explained variance across five theoretically ordered blocks: demographic variables (R² = .045), experiential background (R² = .124), personality traits (R² = .24), cognitive-temporal mechanisms (R² = .307), and, finally, experimentation (R² = .435). Experimentation emerged as the strongest predictor (β = .52, p < .001), while polychronicity maintained significance in the final model. Personality traits, gender, age, and innovation training were not significant once proximal mechanisms were incorporated. The findings support a progressive activation structure in which entrepreneurial intention is primarily associated with mechanisms proximate to behavioral engagement under uncertainty, rather than with traits or distal conditions. These results have direct implications for curriculum design in engineering, suggesting that formative experiences centered on iterative experimentation and parallel coordination of activities may play a decisive role in strengthening entrepreneurial intention.