Tecnology business, inovation and entrepenuership ind industry 4.0

Abstract

In this chapter, entrepreneurship intentions for short and medium terms of university students based on the relationship with multiple intelligences patterns are analyzed using an artificial neural network. In a particular way, the artificial neural network uses Pearson’s correlation coefficient and statistical information to define many entrepreneurship conditions related to intelligence conditions. Thus, many important findings reveal that not all multiple intelligences have a direct and proportional impact on entrepreneurship intention in the short and medium terms. In fact, musical intelligence, intrapersonal intelligence, and naturalistic intelligence present the greatest impact on entrepreneurship intentions in the short term. While visual-spatial intelligence, bodily-kinesthetic intelligence, and naturalistic intelligence present the greatest impact on entrepreneurship intentions in the medium term. The paper contributes to the literature on the deep understanding of the entrepreneur’s behavior concerning strengths and weaknesses of their multiple intelligences. Besides, this multidisciplinary empirical work contributes to improve the design of methods and techniques to strengthen entrepreneurship from the earliest stages of the students’ lives.