1. Introduction
Recent research on entrepreneurship education underscores the need for a better understanding of the complexity and dynamics of the entrepreneurial learning process. This research stream maintains that, in addition to understanding cognitive processes, the interaction between affective and conative constructs is essential to analyze entrepreneurial behavior [
1,
2,
3,
4,
5]. The entrepreneurship phenomenon and the interest to know more about entrepreneurial characteristics have led researchers around the world to increase scientific production that tries to understand the factors and different dimensions of entrepreneurship [
6,
7] Among them, a fertile line of studies related to entrepreneurial intention. Literature defines entrepreneurial intention (EI) as the identification of the conviction to create a business and conscious planning for its realization in a future time [
8].
Starting a business requires individuals to do planned work. Besides the individual’s value system, their culture, social, family, and educational environment can shape the desire to create or not create their own company [
8]. However, given that the creation of companies involves the planning of behavior on the part of the individual, the literature has shown that the behavioral intention models; considering aspects about culture, social, educational, and family environment; are robust in this field of research on entrepreneurial intention [
9]. In particular, the Theory of Planned Behavior (TPB) [
10,
11], had been widely used in various areas to predict different types of behavioral intentions [
12,
13,
14,
15,
16]. As many authors claim, TPB constitutes the most widely used model in the study of EI in different countries [
17,
18,
19,
20,
21].
EI literature had been systematically measuring how individuals’ self-efficacy, subjective norm, and attitude explain entrepreneurial behavior. The present study inquiry is about one EI dimension related to EI, which is gender. There is countless research that has indicated the interest in studying the effect of gender on the entrepreneur intention [
22,
23,
24,
25,
26]. Literature shows controversial results about the differences between male and female EI measures. The issue of gender EI differences had been tested for a variety of groups and individuals. Some studies indicate that there are gender differences in the propensity towards entrepreneurial activity and business initiatives [
27,
28]. For example, Tsui [
29] demonstrates that women perceive a higher degree of fear of failure and a lower degree of self-efficacy than males in the USA and Belgium. Other studies, such as Wilson, Kickul, and Marlino [
30] find gender effects on entrepreneurial self-efficacy examining in two sample groups of adolescents and adult Master of Business Administration (MBA) students [
30], explain that the females present a higher level of self-efficacy that leads to a higher degree of EI.
Further, literature on entrepreneurship considers that university students conform to a community with high entrepreneurial potential [
31]. Additionally, student samples are a good way to represent aspects of society’s potential entrepreneurial activities [
32]. Considering differences in gender EI and the university student entrepreneurial potential, this study revisits the controversy about the effect that gender has on IE, measuring the result in the university community. Accordingly, this study seeks to answer the possible gender differences in entrepreneurial intention in a population of administration and economics students in Chile.
The study presents a case about a university coastal campus. This city, Viña del Mar, is well known for its level of tourism and entrepreneurship related to leisure in the summer seasons. Researchers applied an instrument developed by Rueda, Moriano, and Liñán [
33]. This instrument measures IE using an entrepreneurial intention questionnaire (CIE). The sample surveyed corresponds to 435 economics and administration students in the city of Viña del Mar, belonging to a population of 867, with a response rate for the applied instrument of 50.17% undergraduate students of that study program at the headquarters of Andres Bello National University (UNAB). This university is a secular and private institution created in 1988 and which is characterized by admitting students of all creeds and diverse disciplines. The university has been classified as a massive university, oriented to undergraduate training, whose students come mainly from emerging social sectors [
34,
35,
36]. It is important to mention that the administration and economics program has a national femininity index distributed by 45% of women and 55% of men [
37,
38].
Results show that there are no significant gender differences in entrepreneurial intention levels. Furthermore, there is no evidence for gender differences within any of three entrepreneurial intention factors, i.e., (a) attitudes, (b) subjective norms, and (c) control of perceived behavior.
3. Methodology
Authors use the entrepreneurial intention questionnaire (CIE) to measure EI. Rueda, Moriano and Liñán [
33] developed this EI measurement instrument [
81] and validated their questionnaire for the Latin American context. Similarly, Laguía et al. [
81] commented that CIE is widely used in various LA IE contemporary studies [
82,
83,
84,
85,
86,
87,
88,
89] (The complete questionnaire is in
Appendix A). The authors applied the survey to 435 economic and business students in the city of Viña del Mar. Those students belong to a population of 867 undergraduate students from Andres Bello University located at Viña del Mar city.
The authors used SPSS 23 (IBM, New York, NY, USA) to analyze the 15-item CIE questionnaire. To measure confidence levels, the authors applied the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO). Moreover, the authors used Bartlett’s test of sphericity to identify items belonging to the three (3) factors within the scale as a form of exploratory factor analysis (EFA) with extraction method, unweighted least squares (ULS), and rotation method, Oblimin with Kaiser normalization [
90]. Then the authors analyzed the CIE factors utilizing a confirmatory factor analysis (CFA) with FACTOR software (see
Appendix C) [
91]. The authors used the Hull method for selecting the number of common factors [
92], considering a dispersion matrix with polychoric correlations. Such polychoric correlations are a method for factor extraction unweighted least squares (ULS) and a rotation to achieve Normalized Direct Oblimin simplicity factor [
93,
94]. Before the measurement of normalized direct Oblimin simplicity factor, the authors calculated KMO and Bartlett’s test on the resulting factors [
95,
96]. The expected mean value of RMSR (root mean square residual) is equal to 0.0481 under Kelley’s criterion, it is acceptable for the model [
96] (p. 146). Results were weighted by the set of eigenvalues, accounting for the entrepreneurial intention of the group of students analyzed [
97] (p. 44). Authors compared each factor by gender differences.
Researchers produced a data set through the CIE survey and then analyzed it with cross tables, given the high presence of ordinal or categorical variables. Researchers used a non-parametric correlation coefficient tau-b (τb) of Kendall. Researchers use τb to measure the strength and direction with which two variables of these characteristics are associated. That is to measure the ordered range correlation without defining any sense of causality between those variables. Researchers selected a non-parametric alternative to Pearson’s correlation studies and Spearman’s rank-order non-parametric correlation coefficient [
98]. The Tau-b test was applied, whose correlation is significant for a
p-value at the 0.01 level -in 2 tails, statistically demonstrating an effect [
99].
4. Results
After the exploratory factor analysis of the original 15 variables data set, researchers run an exploratory factor analysis (EFA). The authors preserved 12 variables from their EFA. Authors use SPSS 23 to obtain a KMO of 0.816 and Bartlett’s test with a Chi-square of 1983.926 with 66 degrees of freedom and a significance level of 0.000 for the three factors CIE instrument. The authors achieved a 54.096% explained variance proportion (see
Appendix B).
Additionally, the authors satisfactorily adapted the 12 variables analyzed data set for 12 variables to confirmatory factor analysis (CFA) with the use of the FACTOR software. The CFA obtained a KMO-Kaiser-Meyer-Olkin-equal to 0.82195 (>0.8) and Bartlett’s test of sphericity with a Chi-Square 2905.2 with 66 degrees of freedom and a significance level of 0.000010. Those results are significant and good enough to present the adequacy of the polychoric correlation matrix.
The Hull method for selecting the number of common factors, implemented with a goodness-of-fit index (GFI) with common part accounted for (CAF) and a method for dimensions’ extraction (ULS) where the cumulative percentage of variance explained by the three factors of 71.811%, a GFI = 0.997, Bentler’s simplicity index (S) = 0.99956, Loading simplicity index (LS) = 0.81608, Root Mean Square of Residuals (RMSR) = 0.0287.
The authors reduced the CIE questionnaire according to its latent variables in three factors. Those factors weighted by the set of eigenvalues account for the entrepreneurial intention of the group of students analyzed. Researchers compared each of these three factors by gender, Intention Entrepreneurship (see
Table 1), Entrepreneurship Self-Efficacy (see
Table 2), Attitude towards Entrepreneurship (see
Table 3), and Subjective Norm (see
Table 4).
Each subscript letter denotes a subset of gender categories whose column proportions do not differ significantly from each other at the 0.05 level. An asymptotic standardized error of 0.046 implies not assuming the null hypothesis. Approximate T −0.540 using the asymptotic standard error implies assuming the null hypothesis. The approximate significance is 0.589.
Each subscript letter denotes a subset of gender categories whose column proportions do not differ significantly from each other at the 0.05 level. An asymptotic standardized error of 0.045 implies not assuming the null hypothesis. Approximate T −0.921 using the asymptotic standard error implies assuming the null hypothesis. The approximate significance is 0.357.
Each subscript letter denotes a subset of gender categories whose column proportions do not differ significantly from each other at the 0.05 level. An asymptotic standardized error of 0.047 implies not assuming the null hypothesis. Approximate T 0.297 using the asymptotic standard error implies assuming the null hypothesis. The approximate significance is 0.766.
Each subscript letter denotes a subset of gender categories whose column proportions do not differ significantly from each other at the 0.05 level. The asymptotic standardized error is 0.046, therefore, not assuming the null hypothesis. Approximate T −1.338 using the asymptotic standard error assuming the null hypothesis. The approximate significance is 0.181.
5. Discussion
Entrepreneurial behavior, and more generally entrepreneurship, has long been a theoretical concern among economists and business scholars [
100]. As Krueger et al. [
18] argue, business intentions are one of the most important predictors of the new business behavior of individuals of both genders. The present research shows that there are no significant differences regarding gender entrepreneurial intention. Besides, there are no differences in the variables of self-efficacy, subjective norm, and entrepreneurial attitude, when measured by each gender. These findings reinforce some similar results in the literature on entrepreneurial intention [
101,
102,
103,
104].
Contrary to some literature findings, which have shown gender differences in entrepreneurial intentions for different countries and continents, this research presents non-significant differences. Studies have shown that EI in the US presents a positive orientation in men [
105]. On the other hand, some studies in Asia and Africa have indicated that self-efficacy [
106,
107] presents a greater female entrepreneurial intention than in males. Furthermore, this study presents research results that are in contrast with those obtained from the GEM study, which has shown that the self-efficacy dimension presents higher levels in the case of the female gender within the measurement of entrepreneurial intention [
42,
108], showing progress in sustainable development linked to gender equality (SDG 5).
All in all, the analyzed data set show a higher entrepreneurial intention. The sample presents over 50% of EI for both genders. Such a result makes it possible to conjecture that education for entrepreneurship is an element that positively affects the level of entrepreneurial intention, as shown in the literature [
5,
109]. This effect may be related to the sample type, a sample that researchers selected in a business school. Furthermore, entrepreneurship classes could be affecting the level of business student intentions [
41,
57,
58]. Authors agree with Fayolle [
44] that research on educational variables such as pedagogies and learning objectives and their effects on gender differences with EI measures could be a fertile place for future research, deepening the effects of quality education (SDG 4) that improves gender equality (SDG 5) and, in general, allows for the reduction of inequalities (SDG 10).
6. Conclusions
The article contributes in three aspects, first, guided by the literature, it improves understanding of gender and its effects on Intention Entrepreneurship (see
Table 1), Entrepreneurship Self-Efficacy (see
Table 2), Attitude towards Entrepreneurship (see
Table 3), and Subjective Norm (see
Table 4). In which, it was found that there is neither evidence for gender differences in any of three entrepreneurial intention factors IE, attitudes, subjective norms, and control of perceived behavior, in economics and administration students from a Latin American country. Second, a political point of view, since in Latin America due to the different sociocultural influences, the role of women in society continues to evolve in people’s consciousness and where this study provides us with elements that put men on equal footing to the promotion and support of women in entrepreneurship. Finally, from a practical point of view, this study contributes to greater social sustainability, being able to be used as an argumentative basis for the creation of quality programs in entrepreneurial education (SDG 4) that achieves equal opportunities for men and women (SDG 5), eliminating gender differences in their entrepreneurship intention, and reinforcing equal access to opportunities generated by entrepreneurship in massive educational contexts that are oriented to socioeconomically emerging sectors (SDG 10).
In terms of limitations, the study shows a limited case and further research must be done to generalize researchers’ findings. Additionally, this paper’s results open further possibilities to raise questions about cultural factors that could explain differences between the case of this economics and business students and previous literature reports on gender IE differences in Latin American contexts and compare with other academic programs in different disciplines of knowledge and in various university contexts.