Gender equality in education: an analysis of entrepreneurial behavior in technological colleges in a developing country

ABSTRACT

The article analysed the differences in the influence of entrepreneurial characteristics on entrepreneurial intention according to gender in technological higher education education in a developing country. The methodology used was quantitative, with multivariate data analysis through structural equation modelling. The sample consisted of 604 students of technological higher education from the São Paulo State Technological Colleges. The results proved that the female gender had a more intense influence on self-efficacy and persistence influence on entrepreneurial intention. The male gender had a more significant influence on the relationship between sociability and entrepreneurial intention. For technological higher education institutions to implement an effective entrepreneurial education, it is fundamental to encourage entrepreneurial characteristics differently between genders. Developing and fostering entrepreneurship among women in higher technological education requires a deeper understanding of the female entrepreneurial profile.

KEYWORDS:

• Female entrepreneurship
• entrepreneurial characteristics
• entrepreneurial intention
• technological colleges
• sustainable development goals

Introduction

Across the great majority of countries, the proportion of adult females participating in entrepreneurship is lower than that of adult males in the vast majority of the countries (Bosma et al., 2020; Liñán et al., 2024). It includes Brazil and Latin America, where female participation in new business creation is much lower than that of males (GEM, 2023; Pelegrini & Moraes, 2022). Gender equality in creating new businesses would provide opportunities for economic and social development. When evaluating financial investments in businesses in their initial phase, there is also evidence of differences by gender, revealing that the proportion of female entrepreneurship has reduced. When analysing the longevity of businesses, the male rate is higher (GEM, 2023).

The development and stimulation of entrepreneurship have the university as one of its pillars (Campos et al., 2021; Muscio & Ramaciotti, 2019; Saeed et al., 2015). The dynamics of each university context shape how its community forms its entrepreneurial profile and intention. Research has provided empirical evidence on the positive effects that university educational support structures play on teaching skills and inspiring the right entrepreneurial mindset in students (G. H. S. M. Moraes et al., 2023; Rideout & Gray, 2013), but there is still no consensus on the most effective way to encourage university entrepreneurship (Fischer et al., 2019; G. H. S. M. Moraes et al., 2020; Polin, 2023).

In the university environment, entrepreneurial intention is one of the leading indicators to measure entrepreneurship (Campos et al., 2021; Costa et al., 2023; Polin, 2023). Entrepreneurial intention is a condition that precedes the action of starting a business, and several factors can influence this intention (Krueger et al., 2000). A. K. L. Rocha et al. (2023) compared models to assess entrepreneurial intention in the university environment with more than 1000 students, comparing self-efficacy with a set of entrepreneurial characteristics (risk-taking, planning, opportunity recognition, persistence, sociability, innovation, and leadership) and the results indicated that entrepreneurial characteristics are more appropriate, as they present a greater explanatory factor, a more robust model and also more sensitive for testing differences between groups.

Individual entrepreneurial characteristics appear positively related to entrepreneurial intention in the literature (Campos et al., 2021). Despite significant gaps in the literature related to gender and entrepreneurial intention (Costa et al., 2023; Kyriakopoulos et al., 2024; Polin, 2023), as well as gaps in the literature regarding the role of gender in the relationship between entrepreneurial characteristics and entrepreneurial intention (Amofah & Saladrigues, 2022; Cacija et al., 2023; Krakauer et al., 2018; Pelegrini & Moraes, 2022). Therefore, this gap is more evident in developing countries, which tend to emulate advanced economies with little adaptation to their particularities (Krakauer et al., 2018; Pelegrini & Moraes, 2022; Ramadani et al., 2022), and specially in the technological higher education.

Furthermore, within the comprehensive set of 17 Sustainable Development Goals (SDGs), which establish a universally accepted framework encompassing key areas of action to foster more peaceful, equitable, and resilient societies, two of these goals are directly linked to education and gender: SDG 4 - Quality Education and SDG 5 - Gender Equality. SDG 4 emphasises that by 2030, every student should possess the knowledge and skills necessary to actively promote sustainable development, including the crucial aspect of gender equality, among other vital themes (United Nations, 2015). Conversely, SDG 5 centres around the equal worth of men and women and endeavours to achieve gender parity, aiming to empower all women and girls through six specific objectives, with education serving as the primary catalyst for transformative change (Miralles-Cardona et al., 2022; UN, 2015).

In this context, the article aims to analyse the differences in the influence of entrepreneurial characteristics on the intention to undertake according to gender in a developing country. More specifically, we intend to verify whether the influence of entrepreneurial characteristics (self-efficacy, identifying opportunities, innovation, leadership, persistence, planning, and sociability) on the intention to undertake differs between males and females in technological higher education in São Paulo. The research question is: What are the differences between genders in the influence of entrepreneurial characteristics on entrepreneurial intention?

Theoretical background

Entrepreneurial intention

The literature on entrepreneurship seeks to understand the key points for the emergence of new businesses. Through theoretical models, entrepreneurial intention is explored as the main characteristic of entrepreneurial behaviour. Considering that the decision to undertake is based on intentional behaviour and particular motivations, the models seek to understand what precedes such intentions in real behaviour (Schlaegel & Koenig, 2014)

The models of Ajzen (Theory of Planned Behaviour-TPB) and Shapero (Entrepreneurial Event) interconnect self-efficacy (perceived behavioural control and perceived viability), in which perceived control encompasses external control factors, such as resources, opportunities, and potential barriers, and reflects the perception that it depends exclusively on the individual for such achievement. Ajzen’s other measures linked to subjective norms and intention correspond to Shapero’s perceived viability. However, the intention may not be enough. Shapero adds volitional conduct, linking the propensity to act, as an explanation for why business founders initially said they didn’t intend to start a business. There is debate regarding entrepreneurial stereotypes, cultural differences, and whether social influences can mediate intentions (Krueger et al., 2000).

According to Maes et al. (2014), gender differences can be explained by perceived behavioural control and personal attitude factors, but not by social norms. In order to stimulate female entrepreneurship, the study reinforces suggestions by strengthening women’s personal belief in their capacity, changing entrepreneurship values associated with family balance to a context of achievement and achievement value, and studying models of female entrepreneurial intention.

Studies have examined the direct effect of gender on entrepreneurial intentions (Schlaegel & Koenig, 2014; Shinnar et al., 2012; Shneor & Jenssen, 2014). In other studies, however, gender was analysed as a moderator of relationships involving entrepreneurial intention (Kyriakopoulos et al., 2024; Shirokova et al., 2016).

An explanation for such inconsistencies could be that gender was treated as an independent variable whose effect on intention was fully mediated by other intervening variables. In contrast, in other studies, gender was treated as a moderating variable (Shneor & Jenssen, 2014).

Entrepreneurial characteristics

Entrepreneur characteristics research identifies the set of characteristics that elevate entrepreneurial potential, as well as the tools that can be used to measure entrepreneurial profiles (Cacija et al., 2023; G. H. S. M. D. Moraes et al., 2018; A. K. L. Rocha et al., 2023; Shirokova et al., 2016). Specifically, this study will focus on characteristics associated with human behaviour, particularly gender-related characteristics.

From existing definitions in the literature, attitudinal characteristics common to the entrepreneurial profile and differences related to gender aspects will be used to build the hypotheses. Thus, the characteristics under study include: self-efficacy, risk taking, innovation, leadership, persistence, planning, identifying opportunities, and sociability (Pelegrini & Moraes, 2022; Schmidt et al., 2022)

Although some models of entrepreneurial intention in the literature use only one or some of the characteristics to explain entrepreneurial intention (G. H. S. M. D. Moraes et al., 2022; Pittaway & Edwards, 2012), in a comparison between different models, A. K. L. Rocha et al. (2023) proved that using all entrepreneurial characteristics is more appropriate, making the model more robust and more sensitive for multigroup or moderation analyses.

The academic literature in the late 1970s began the study of gender in entrepreneurship, mainly on the entrepreneurial characteristics of the female gender in developed countries (Krakauer et al., 2018).

A few studies have shown that the similarities between genders are more significant than the differences between them (Porfírio et al., 2023). De Vita et al. (2014), in the study on the characteristics of the female gender in developing countries, identified lower rates of business creation, innovation, and less competitive results compared to the market. Through empirical findings, the authors highlight the influence of religion, business training, and access to business support networks as the main influences of the lower participation of the female gender in entrepreneurship. Shirokova et al. (2016) suggest that the male gender results more in entrepreneurial intention in entrepreneurial action. Thus, while both genders seem equally committed to an entrepreneurial career, the male gender seems more engaged in creating new companies.

In the quest to understand the differences, studies point to the development of human capital as the main factor, mainly due to training gaps and limited access to initial capital in enterprises. Other lines of research suggest that differences may be related to the social and cultural construction of gender. Other probable explanations compare results of enterprises linked to lower internal control, limitation of personal beliefs of capacity, environment, and more significant barriers to credit and social recognition (Shirokova et al., 2016; Tsai et al., 2016; Verheul et al., 2012)

In this context, the central hypothesis of the study is presented:

Hypothesis 1:

There are gender differences in the influence of entrepreneurial characteristics on entrepreneurial intention.

The sub-hypotheses of the research are related to the relationships between each of the characteristics with the entrepreneurial intention, being:

Hypothesis 1a:

There is a difference between genders in the influence of self-efficacy on entrepreneurial intention.

Hypothesis 1b:

There is a difference between genders in the influence of taking risks on entrepreneurial intention.

H1c.

There is a difference between genders in the influence of innovation on entrepreneurial intention.

Hypothesis 1d:

There is a difference between genders in the influence of leadership on entrepreneurial intention.

Hypothesis 1e.

There is a difference between genders in the influence of identifying opportunities on entrepreneurial intention.

H1f.

There is a difference between genders in the influence of persistence on entrepreneurial intention.

Hypothesis 1g:

There is a difference between genders in the influence of planning on entrepreneurial intention.

Hypothesis 1h:

There is a difference between genders in the influence of sociability on entrepreneurial intention.

Methodological aspects

The article employed multivariate data analysis, specifically employing the Partial Least Squares Structural Equation Modeling technique (PLS-SEM). This approach was chosen in light of the research’s aims to elucidate gender-based distinctions in the relationships among the presented constructs, conceptualised as latent variables. Consequently, a multigroup analysis, as expounded by Hair et al. (2022), was conducted. The computations integral to this analytical framework were executed using SmartPLS 4.0 software.

The conceptual model is composed of 9 reflexive constructs (latent variables), one being the dependent variable (entrepreneurial intention) and eight independent variables (self-efficacy, taking risks, innovation, leadership, identifying opportunities, persistence, planning, and sociability). In addition, it presents a binary variable (male and female gender) that analyzes the differentiation between relationships (multigroup analysis).

The research questionnaire used several types of research on entrepreneurship and gender as a reference. Table 1 presents the research questions.

Table 1. Data collection instrument and conceptual basis.

Construct	Question	References
SE1	I can work productively even under stress, pressure, and conflict.	De Noble et al. (1999); Newman et al. (2019)
SE2	I can originate new ideas and products.
SE3	I can develop and maintain favourable relationships with potential investors.
SE4	I can see market opportunities for new products and services.
SE5	I can recruit and train key employees in the company.
SE6	I manage to develop a work environment that encourage people to try something new.
SE7	I have the skills to lead a new business opportunity.
RT1	I would assume a long-term debt, believing in the advantages that a business opportunity would bring me.	E. L. D. C. Rocha and Freitas (2014); Schmidt and Bohnenberger (2009)
RT2	I accept taking risks in exchange for possible benefits.
RT3	My decisions are not predominantly based on my comfort zone.	G. H. S. M. D. Moraes et al. (2018)
RT4	I believe that getting involved in higher risk situations will lead to more impactful results.
IO1	I believe I have a good ability to detect business opportunities in the market.	Krakauer et al. (2018)
IO2	I believe I have the ability to understand, recognise and make use of concrete of abstract, implicit and constantly changing information.	Markman and Baron (2003)
IO3	I believe I am capable of taking advantage of any and all opportunities to evaluate businesses.	Krakauer et al. (2018)
IO4	I believe I have the ability to identify and evaluate business opportunities.
IN1	I prefer a job full of novelties to a routine activity.	E. L. D. C. Rocha and Freitas (2014); Schmidt and Bohnenberger (2009)
IN2	I like to change my way of working whenever possible.
IN3	I like to improve the conventional and correct way of activities, not strictly following steps.	Schmidt and Bohnenberger (2009)
IN4	I bet on creativity when designing projects/activities.
LE1	I am often chosen as a leader in school or professional activities.	E. L. D. C. Rocha and Freitas (2014); Schmidt and Bohnenberger (2009)
LE2	People respect my opinion.
LE3	I can convince people to overcome conflicts and work as a team to achieve a certain result.
LE4	I am able to encourage people to carry out tasks for which they are unmotivated.	Schmidt and Bohnenberger (2009)
LE5	People often ask my opinion on matters of work or study.
PE1	Professionally, I consider myself a much more persistent person than the others.	Schmidt and Bohnenberger (2009)
PE2	I am able to work intensively on projects, even social deprivation may occur, even if these have uncertain returns.	Markman and Baron (2003)
PE3	I believe I have the ability to create, lead and implement new life plans.	Rocha and Freitas (2014)
PE4	Whenever possible, I carry out a self-assessment, taking perseverance, imagination and creativity as points to be analysed.
(PL1)	I always plan everything I do very well.	E. L. D. C. Rocha and Freitas (2014); Schmidt and Bohnenberger (2009)
(PL2)	I define where I want to go and detail all the steps I must follow.
(PL3)	I know I can define my short, medium and long term paths.	G. H. S. M. D. Moraes et al. (2018)
(PL4)	I like to set goals and targets to feel challenged.
SO1	The social contacts I have are very important for my personal life.	E. L. D. C. Rocha and Freitas (2014); Schmidt and Bohnenberger (2009)
SO2	I know several people who could help me professionally if I needed it.
SO3	I relate very easily with other people.
SO4	I try to keep in constant contact with people in my network.	G. H. S. M. D. Moraes et al. (2018)
EI1	I’m ready to do anything to be an entrepreneur.	Linán and Chen (2009); G. H. S. M. D. Moraes et al. (2018)
EI2	Even if I work for other companies, I will never abandon my dream of opening my own business.
EI3	My biggest accomplishment will be having my own business.
EI4	I will make every effort to create and maintain my own company.
EI5	I intend to open a company in the coming years.

Sample aspects

The research analyzes the Technological Colleges of the State of São Paulo (Fatecs). The justification for the choice is the importance of the state of São Paulo for the country and the importance of Fatec in the state. São Paulo has the highest Gross Domestic Product (GDP) per capita in Brazil, and the highest population density, with more than 45 million people. It also presents the best results regarding the development of primary education, being the 12th largest state in the area. The state is the most crucial metropolitan region in the country. Regarding technological higher education, the teaching modality grew the most in the country in recent years, with a growth of 11.5% from 2018 to 2019 and an accumulated growth of more than 200% in the last decade. Currently, technical higher education students correspond to 14.2% of Brazil’s total students enrolled in undergraduate courses (INEP, 2022).

The research collected data from technological education, comprised of units of the Colleges of Technology (Fatec) located in Americana, Araras, Indaiatuba, and Piracicaba.

The data collection instrument was applied in person through a printed questionnaire between February and March 2020. It should be noted that the collection took place before the stoppage of face-to-face classes due to the COVID-19 pandemic. In total, 631 completed questionnaires were obtained, 27 of which were considered inadequate because they had a lot of missing data. Thus, the final sample consisted of 604 questionnaires validated for the Fatecs sample.

The average age of the students was 23.86 years old, with a standard deviation of 5.5 years old. The predominant age group of respondents includes 20 to 30 years. The youngest participant was 18 years old, and the oldest was 63 years old. Regarding marital status, 81% of respondents were single, 11.5% were married, and 7.5% had other unspecified options. Regarding gender, 51% were female, 48.7% were male, and 2 participants identified as non-binary.

Results analysis

The initial empirical phase involved assessing the measures outlined in the conceptual model. As certain indicators were adapted from prior studies, Confirmatory Factor Analysis (CFA) was essential to confirm whether the chosen indicators effectively captured the constructs. Consequently, CFA was executed using the SmartPLS 4 software. Following the recommendation by Hair et al. (2022) to maintain factor loads at or above 0.7, indicators exceeding 0.4 but less than 0.7 were considered acceptable if they did not impact the Average Variance Extracted (AVE) and Composite Reliability (CC) values. Consequently, some indicators were excluded based on this criterion. The results of the CFA can be found inTable 1.

Then, we evaluated the measurement model, which has nine reflective constructs (self-efficacy, taking risks, innovation, leadership, identifying opportunities, persistence, planning, sociability, and entrepreneurial intention). According to Hair et al. (2022), the criteria for evaluating reflective constructs are the internal consistency of the model’s indicators, the reliability of the indicator, and convergent and discriminant validity.

Thus, the crossed-loading factors of the construct indicators were initially verified. In this analysis, the loads between the indicators of the same construct must be greater than 0.7, and this is a convergent analysis indicator. Values between 0.4 and 0.7 are also considered valid. However, it is also necessary to assess whether these indicators are essential for the extracted mean-variance and composite reliability indicators (Hair et al., 2022). At this stage, some indicators of the constructs had to be excluded (AE1, AR3, IN3, and PE2). All indicators have higher values in the construct than in the other constructs, which allows verification of the discriminant analysis.

For convergent validity, another widely used criteria are the average variance extracted (AVE). The AVE value must exceed 0.50 (Hair et al., 2022). Two indicators are usually used for internal consistency: Cronbach’s alpha and composite reliability. For Cronbach’s alpha, values above 0.60 are typically acceptable in exploratory studies (Hair et al., 2022). For composite reliability, values must be greater than 0.70 (Hair et al., 2022). Another indicator used to analyse the discriminant validity is the value of the square root of the AVE, which must have values more significant than the correlation between the latent variables (Hair et al., 2022). Table 2 shows all these indicators, which are within the established by the authors.

Table 2. Evaluation of the measurement model.

Constructs	SE	RT	OR	IN	LE	PE	PL	SO	IE
Self-efficacy	0.72
Risk taking	0.306	0.742
Opportunity recognition	0.65	0.449	0.789
Innovation	0.382	0.377	0.408	0.716
Leadership	0.457	0.322	0.49	0.358	0.714
Persistency	0.528	0.392	0.619	0.486	0.528	0.748
Planning	0.339	0.321	0.471	0.339	0.54	0.532	0.728
Sociability	0.366	0.327	0.433	0.271	0.509	0.397	0.372	0.719
Entrepreneurial Intention	0.527	0.392	0.653	0.326	0.331	0.509	0.264	0.354	0.868
Cronbach’s Alpha	0.814	0.592	0.797	0.529	0.762	0.606	0.714	0.686	0.918
Composite Reliability	0.865	0.786	0.867	0.759	0.838	0.791	0.818	0.810	0.939
Average Variance Extracted	0.518	0.550	0.623	0.512	0.509	0.56	0.53	0.517	0.754

For the evaluation of the structural model, the first step was to verify the collinearity of the structural model. Thus, the variance inflation factor (VIF) values were evaluated for each subsection of the structural model. No value was equal to or greater than 5, all within the range established by Hair et al. (2022).

Next, the bootstrapping technique was used to analyse the significance of the relationships (Hair et al., 2022). The results indicate that only the relationships between innovation and leadership with entrepreneurial intent were not confirmed. All other relationships are significant.

Continuing the analyses, the coefficient of determination (R²) was analysed. According to the analyses, the complete model presented an R² of 48% for the entrepreneurial intention construct, which is considered high. The Q² values (an indicator of predictive relevance) were also evaluated. For this, the blindfolding procedure (distance omission) was used. For Hair et al. (2022), values greater than zero indicate the predictive relevance of the path model. In the case of this article, the values are within the established.

Before analysing the differences between the groups, we analyse the invariance of their measurements. For this, the Measurement Invariance Assessment (MICOM) analysis procedure was used in a three-step approach, with the analysis of configural invariance, compositional invariance, and the equality of composite mean values and variances (Hair et al., 2024), with SmartPLS 4 software. The results are within the recommendations of Hair et al. (2024), indicating that group relationships are invariant and we can run multigroup analysis. Thus, a multigroup analysis was performed to test the study’s hypotheses, which concern differences between relationships in different genders (Hair et al., 2022).

The results indicate a significant difference in the relationships between the constructs in terms of gender in the three associations. In the relationship between self-efficacy and entrepreneurial intention, the effect is positively more intense for females, as in the relationship between persistence and entrepreneurial intention. As for the influence of sociability on entrepreneurial intention, the male gender is more intensely positive. Thus, the results partially confirm our central hypothesis, confirming sub-hypotheses H1a, H1f, and H1h.

The results did not show significant differences between genders in the relationship of taking risks with entrepreneurial intention. The influence is positive and significant in both cases, slightly higher in males. Despite the results of this research pointing to a lower risk propensity for the female gender, this difference was not significant, which, in a way, contradicts previous studies.

The constructs of innovation and leadership showed unexpected results regarding the influence on entrepreneurial intention. Both in the female gender (Figure 1) and in the male gender (Figure 2), the relationships were not significant. The results did not show significant gender differences in the relationship between identifying opportunities and entrepreneurial intention. The influence is positive and significant in both cases, being higher in males. Thus, despite this research pointing to a more significant influence of identifying male gender opportunities, the difference is insignificant, which contradicts previous research.

Figure 1. Resulting model – female gender.

Figure 2. Resulting model – male gender.

The planning latent variable negatively and significantly influenced the intention to undertake in both genders. Despite the literature pointing to a positive influence of planning on entrepreneurial intention, planning is strongly influenced by entrepreneurial activities pre-existing, which is not the case of the present study, in which most students had no entrepreneurial experience.

To highlight the differences, Figures 1 and 2 show the resulting models for females and males.

Discussion

The main objective of this article was to investigate the differences in the influence of entrepreneurial characteristics on the intention to undertake according to gender. Just as entrepreneurship promotes economic and social development, gender equality in business creation can enhance financial results and solutions and improve the quality of life for society (GEM, 2023).

In a relatively understudied domain, namely technological higher education, this study presents substantiated evidence about gender differences in entrepreneurial behaviour. Based on a systematic analysis of three examined associations, a noteworthy variance was found, which corroborated prior research indicating distinct entrepreneurial behaviours among genders, particularly in terms of factors influencing entrepreneurship (Maes et al., 2014; Pelegrini & Moraes, 2022; Yukongdi & Lopa, 2017).

Findings indicate that self-efficacy plays a significant role in entrepreneurial intention differently depending on gender. Female cohorts show a positive and statistically significant effect (Figure 1), while male cohorts do not show such an effect (Figure 2). Therefore, female entrepreneurs are more likely to engage in entrepreneurial pursuits when their self-efficacy is enhanced. Interestingly, this outcome differs from previous research, which generally posited higher levels of self-efficacy among men (Casile et al., 2021). The current findings, however, are consistent with an alternate study conducted within the Brazilian context, which indicated a heightened impact of self-efficacy on entrepreneurial intentions among females (Pelegrini & Moraes, 2022).

There are notable gender differentials in the results regarding persistence’s impact on entrepreneurial intention. Females exhibit a positive and statistically significant effect, whereas males do not. Therefore, females with heightened self-appraisals of persistence are more likely to pursue entrepreneurial endeavours. Earlier studies have indicated gender-based variations, particularly regarding perceived risks, shorter business sustainability, and disparities in familial responsibilities affecting women’s access to investments. The combination of persistence and motivational dedication among female entrepreneurs, influenced by familial commitments and a focus on diversity and societal contributions, has exhibited favourable outcomes, fostering gender solidarity and empowerment (Butticè et al., 2022; Schmidt et al., 2022). However, this is the first study with these results in the context of technological higher education.

It was evident that there were gender disparities in the outcomes of the study when it came to the influence of sociability on entrepreneurial intention. Males showed a positive and statistically significant impact, while females did not. There are varying and sometimes inconclusive findings in the literature exploring the role of sociability in entrepreneurial contexts. G. H. S. M. D. Moraes et al. (2018) and E. L. D. C. Rocha and Freitas (2014) found no significant effects of sociability on entrepreneurial behaviour, as opposed to Campos et al. (2021) and A. K. L. Rocha et al. (2023), as well as Krakauer et al. (2018), particularly regarding the female gender. This is the first study with these results in the context of technological higher education, however.

Moreover, the construction of professional relationship networks displays gender-specific patterns, with males exhibiting a propensity to establish networks in male-dominated settings, whereas females tend to cultivate mixed-gender networks. The university milieu, facilitated by educators, assumes a pivotal role in facilitating the development of contact networks among females and fostering supportive networks (Laouiti et al., 2022).

After scrutinising the outcomes of gender-specific model analyses, notable distinctions emerge. Within the resultant model for the female gender, the explanatory factor attains a higher magnitude (R² = 60.3%). The pre-eminent influencers, delineated in descending order of significance, encompass identifying opportunities (factorial loading of 0.376), self-efficacy (factorial loading of 0.319), persistence (factorial loading of 0.280), taking risks (factorial loading of 0.086), and planning (factorial loading of 0.086). In the model derived from the male gender, the explanatory factor was deemed substantial (R² = 40.4%), albeit comparatively lower than that of the female counterpart. The primary influencers, arranged in descending order of significance, include identifying opportunity (factorial loading of 0.481), sociability (factorial loading of 0.201), taking risks (factorial loading of 0.120), and planning (factorial loading of −0.119).

This study fills a significant gap in the literature regarding the role of gender in entrepreneurial intention (Costa et al., 2023; Kyriakopoulos et al., 2024; Polin, 2023). Furthermore, it contributes to the understanding of the relationship between entrepreneurial characteristics and entrepreneurial intentions in the context of technological higher education institutions (Amofah & Saladrigues, 2022; Cacija et al., 2023; Krakauer et al., 2018; Pelegrini & Moraes, 2022). The study contributes to the literature on female entrepreneurship from the perspective of a developing Latin American country by providing valuable information about students’ entrepreneurial behaviour in this type of institution. It is possible to highlight some research contributions based on the results obtained. Firstly, the research demonstrated that there are differences in entrepreneurial behaviour between genders in technological higher education, and the influence of entrepreneurial characteristics on the intention to undertake is significantly more significant in the case of females (R2 of 60.3% in the model female gender versus 40.4% in the model male). Therefore, investing in improving entrepreneurial characteristics in a university environment will result in different outcomes for men and women. Results can be generated more effectively through initiatives that consider gender differences. To improve and elevate female entrepreneurial intentions, entrepreneurship education, and support can focus on the characteristics women feel the least equipped with. Moreover, improving how they perceive the knowledge they obtain (Chowdhury et al., 2019) is necessary.

Second, the characteristics of innovation and planning are critical aspects in the training of higher technological education students. In a country with many new businesses but where the innovation of these ventures is still scarce (G. H. S. M. Moraes et al., 2023), these characteristics are fundamental for those who intend to undertake. In both groups (male and female), the relationship between innovation and entrepreneurial intention was not significant, which implies that the perception of innovative capacity is not a determinant of the student’s intention to start an enterprise. Regarding planning, the relationship with entrepreneurial intention was significant but negative in both groups. This means students who intend to undertake do not feel prepared for planning. Thus, technological higher education environments must consider approaches that encourage innovation and students’ planning ability. This result is consistent with the research by Pelegrini and Moraes (2022), which demonstrates the importance of promoting entrepreneurship in a practical way in the university environment.

This article aims to advance knowledge about entrepreneurial behaviour among women and the context of technological higher education in the country. To prepare the university environment so that entrepreneurship becomes an increasingly important part of the university curriculum, we sought to provide managers and those interested in entrepreneurial education with an accurate understanding of student entrepreneurial behaviour from a practical perspective. Based on the results of this study, it has been confirmed that an effective entrepreneurial education within colleges can be implemented by stimulating the development of entrepreneurial characteristics differently between sexes. We suggest a more practical approach to improve the effectiveness of entrepreneurship efforts. Several activities can contribute to developing these characteristics in students, including technology competitions, hackathons, and business plan competitions (Shah & Pahnke, 2014).

A nuanced comprehension of the entrepreneurial profile of women in technological higher education holds the potential to inform the design of training initiatives directed at cultivating and nurturing entrepreneurship among female individuals. Moreover, such insights can serve as evaluative instruments, enabling women to ascertain their behavioural profiles’ congruence with the entrepreneurial sphere’s demands. This, in turn, facilitates more informed career decision-making. Consequently, the outcomes of this study contribute substantively to the pursuit of sustainable gender equality, aligning with the objectives outlined in Sustainable Development Goal (SDG) 4 - Quality Education and SDG 5 - Gender Equality.

Conclusion and final remarks

The university is one of the main pillars for stimulating and developing entrepreneurship (Campos et al., 2021; Muscio & Ramaciotti, 2019; Saeed et al., 2015). This dynamic is shaped according to the university context, forming the entrepreneurial profile of its students. A university environment with well-developed educational support structures can stimulate an entrepreneurial mindset in different types of students (G. H. S. M. Moraes et al., 2023; Rideout & Gray, 2013).

The article presented a robust model with high explanatory value for entrepreneurial intention and validated the gender difference in a little-explored context: the technological higher education environment. Thus, the research fills a significant gap in gender differences in entrepreneurial behaviour (Amofah & Saladrigues, 2022; Krakauer et al., 2018; Miralles-Cardona et al., 2022; Pelegrini & Moraes, 2022).

Moreover, the research helps address a gap regarding how entrepreneurial education shapes students’ entrepreneurial conduct and intent, particularly within the context of FATECs, as Shi et al. (2020) point out. The study contributes significantly to our understanding of entrepreneurial education outcomes by presenting empirical findings from a coherent sample within a developing nation. According to Sims and Chinta (2019), given the dynamic nature of the entrepreneurship domain, there is ample room for exploring entrepreneurial attitudes, intentions, and actions.

Despite the care and methodological rigour of the researcher, this research has limitations that must be understood for the correct assimilation of the results. The sample is not probabilistic for Brazilian technological higher education, despite being suitable for using the PLS-SEM. The collection was carried out only with students in the administration area, limiting the results’ scope to the entire FATEC public. A secondary database was used, and the questionnaire was not explicitly developed for this article, defining the model’s variables. The collection was carried out with a single cross-section, which makes it difficult to analyse how the variables of interest evolve.

With the limitations presented, some suggestions for future research can be indicated. Other contexts (in Brazil and abroad) and technological higher education courses can be explored, considering the same analysed relationships, allowing comparisons and new analyzes. Longitudinal studies can be developed, addressing gender differences in entrepreneurial behaviour in technological higher education, considering differences in regions or academic courses. Qualitative approaches such as case studies, comparative qualitative analysis, and in-depth interviews can be carried out in different contexts to deepen gender differences.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico [303924/2021-7]; Fundação de Amparo à Pesquisa do Estado de São Paulo [2021/08267-2].

Notes on contributors

Marcela Alessandra de Moraes

Marcela Moraes is a Ph.D. candidate with a master’s degree in Business Administration from the University of Campinas. She works as a professor in Senac, Brazil.

Gustavo Hermínio Salati Marcondes de Moraes

Gustavo Moraes is an associate professor of business administration at the School of Applied Sciences at the University of Campinas and an extraordinary associate professor at North-West University in South Africa.

Izabela Simon Rampasso

Izabela Rampasso is professor at Universidad Católica del Norte, Chile. She holds a M.Sc. and PhD in Mechanical Engineering from the University of Campinas (Brazil). Currently, she conducts research on sustainability, engineering education, and topics related to the management of productive systems.

Antonio Carlos Pacagnella Júnior

Antonio Carlos Pacagnella Júnior is an associate professor of engineering at the School of Applied Sciences at the University of Campinas. He has a PhD in Production Engineering from the Federal University of São Carlos. He also has a degree in Mechanical Engineering from the State University of Campinas.

Diogo de Siqueira Camargo Vasconcelos

Diogo Vasconcelos has a doctorate in Administration from the State University of Campinas, a master’s degree in business administration, a specialist in Marketing, and a Bachelor’s degree in business administration with specialisation in international business from the Methodist University of Piracicaba.

Rosley Anholon

Rosley Anholon is a mechanical engineer with a master’s and a doctorate in materials engineering and manufacturing processes from the State University of Campinas. He has experience in Operations Management, Sustainability, Business Incubation Mechanisms, and Engineering Education.