Keywords

1 Introduction

Vocational education at university is composed of different contents and activities for learning. For this reason, knowing the factors behind certain interests is crucial for the planning of teaching since theoretical components must be combined with practical activities through business actors. The promotion of entrepreneurship by a country is associated with its level of competitiveness and is based on the training of new professionals, so it is critical that universities can play an active role in the generation of entrepreneurship-oriented professionals.

Green entrepreneurship refers to the practice of starting companies that focus on sustainability and social responsibility. Students who engage in green entrepreneurship may do so for personal reasons, such as wanting to make money or gain experience, or they may want to help others. In addition to these motivations, some students choose to pursue green entrepreneurship because they believe it is the right thing to do. Green entrepreneurship is not only a way to make money, but also a way to contribute to society. There are three ways that universities can support green entrepreneurship: (1) providing information about opportunities; (2) providing access to capital; and (3) offering mentorship. Universities should provide information about opportunities for students to participate in green entrepreneurship. Information includes details about the types of business models that exist, what type of funding is available, and how to apply for grants. Providing information about opportunities helps students decide if green entrepreneurship is something they would like to pursue. Therefore, the objective of this study is to measure variables that can explain the intention to implement a green venture. The variables evaluated are conceptual support, such as those developed in universities through promotion and training programs with complementary courses. Likewise, the support given by the country to generate ventures is evaluated, which is explained by the regulation to promote the creation and development of different types of ventures. This support is a central element that has been evaluated, since this implies that the contents of the courses include tools for the development of enterprises, which implies management, marketing, logistics, and local and international regulation. The mediating variable that is part of the study is entrepreneurial self-efficacy, i.e., how convinced the student is of being able to launch and grow a venture. Finally, the student's intention with respect to the generation and development of green businesses is measured.

2 Previous Studies

Table 1 shows relevant studies carried out in different regions on entrepreneurship. Table 2 shows important research developed about green entrepreneurship. Previous evidence is very valuable because it allows us to have the progress of each region or even in each country so that we can have a complete idea of the level of progress, the actions that are being developed mainly in the universities and the strategies that must be implemented to achieve greater implementation.

Table 1 Entrepreneurial education in universities
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Table 2 Green entrepreneurial education in universities
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3 Theoretical Framework

3.1 Theory of Planned Behavior (TPB)

The theoretical basis for this research is Ajzen’s TPB [1] is characterized by evaluating the factors that converge in people’s final behaviors, with intention as the predictor variable of behavior. TPB infers that the intention of a behavior has a very close link with behavior; it is also mentioned that said intention is associated with two basic aspects: social influence and the nature of the person. The social factor is the perception of the social pressure of everyone to perform a specific action; this factor is called “subjective norm”, which is related to the beliefs of significant people for the individual. Thus, when he/she feels that for other people the action is important then he/she will feel that he/she must do it. The personal factor is the evaluation about performing a behavior; this is called “attitude”, which is linked to the consequences that an individual can expect from performing the specific behavior.

3.2 Social Cognitive Theory (SCT)

The SCT developed by Bandura [4] emphasizes that people’s behavior is under their own control, and in this way, they can increase their self-efficacy. In SCT, a person has a self-system that allows them to evaluate control over their feelings and performance. This self-system is used as reference, regulation, and evaluation of behaviors. Thus, this serves as a self-regulatory function to convert individuals with the capacity to influence their own cognitive processes and actions and thus alter their environment. The model of the current study has been developed by the authors to evaluate how different types of support existing in the educational ecosystem, and at the governmental level, have an effect on students’ entrepreneurial self-efficacy to increase green entrepreneurship intention. The combination of these factors is based on the planning that can be generated in universities to achieve an entrepreneurial ecosystem, involving students and professors, based on field results, with a focus on business, social and environmental sustainability.

4 Hypothesis

Green entrepreneurial intention (GEI)

Intention is the state of the individual that creates decisions, attention, and interest to carry out a specific action [7, 37, 51]. Several factors explain how a person plans a behavior [19]. The intention is the previous step of a behavior. The intention to perform a behavior have a positive effect on the development of entrepreneurship [9, 37, 43, 50]. Entrepreneurship can be developed by individuals or companies [38]. GEI is the implementation of innovative activities related to sustainability, offering products or services based in green process [16].

Country support for entrepreneurship (CSE)

This refers to regulation, in macro and micro level, in a country to promote the entrepreneurship [18]. The variable describes what the person thinks related to the country’s support and promotion of entrepreneurial business initiatives. The perception of banking systems or social programs that can support the start-up of a business venture is also measured, this implies support in the initial process of the venture, bank loans, exemption from certain taxes, business-business-government linkages, among others. Thus, we have the following hypothesis:

H1. CSE has a positive and significant effect on ESE

Institutional support for entrepreneurship development (ISDE)

This variable involves the activities carried out by the educational institution to provide knowledge and promote competencies on business management, so that students are able to experience the theoretical components through involvement with successful entrepreneurs, start-up roundtables, seeking mainly that through non-curricular activities it is possible to generate the strength to create new businesses [17]. To this end, the following hypothesis is formulated.

H2. ISDE has a positive and significant effect on ESE

Entrepreneurial self-efficacy (ESE)

This variable is a person’s belief in his or her ability to perform any activity successfully and incorporate specific behaviors into his or her daily schedule [5, 27]. Entrepreneurial self-efficacy means the confidence of one person to carry out entrepreneurial activities [44, 53]. Research shows the positive influence of entrepreneurial self-efficacy on entrepreneurial intention [12, 28, 34], which can be understood to mean that people who have a high level of self-efficacy are more likely to start businesses. Therefore, the following hypothesis is formulated.

H3. ESE has a positive and significant effect on GEI.

5 Model to Test

Figure 1 show the model to test. The proposed relationship between the variables of the study can be evidenced.

Fig. 1
A model diagram. It represents the relationship between the variables of the study. It is divided into four categories namely institutional support, country support, entrepreneurial self-sufficiency, and green entrepreneurs.

Research model

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6 Methodology

6.1 Sample

The sample is based on university business students in Colombia, older than 18 years. A total of 389 students participated, 176 men (45.24%) and 213 women (54.76%), between 18 and 31 years old (mean = 22.34 years; SD = 5, 65 years).

6.2 Data Collection, Questionnaire and Analysis

To collect the data, it was used an online questionnaire, run online since March 16 to April 30, 2021. The questionnaire collects sociodemographic data and Likert scale data based on previous studies: ISDE [63], CSE (current authors), ESE [57], and GEI [63]. It was used a 5-point Likert-type scale (1 = completely disagree; 5 = completely agree. The analysis was using SmartPLS version 3.3.2.

7 Outcomes

7.1 Reliability

The analysis of internal consistency is showed in Table 3.

Table 3 Reliability of scales
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7.2 Validation with SEM-PLS

The Table 4 include the internal consistency of dimensions using composite reliability, average variance extracted, and discriminant validity.

Table 4 Construct validity of the items
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7.3 Discriminant Validity Using SEM-PLS

It was calculated by the Fornell-Larcker criterion [20]. The fulfillment of this criterion, demonstrating the discriminant validity (Table 5).

Table 5 Discriminant validity of sub-scales
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7.4 Bootstrapping

The bootstrapping outcomes was based in resampling of 5000 times. Table 6 shows that the values are significant (p values < 0.01).

Table 6 Significance of beta coefficients
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Figure 2 shows the research model tested. The results confirm that ESDE, CSDE, and CSE through ESE have an effect on GEI in business students.

Fig. 2
A flow diagram depicts the results of the model testing. The factorial weight of each category is given. G E I 1 to 8 results from I S D E 1 to 9, C S E 1 and 2 and E S E 1 to 4.

Research model evaluated

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7.5 Test of Hypothesis

  • Hypothesis 1 (H1): CSE has a positive and significant effect on ESE

    CSE has a positive effect of 0.161 on ESE. The hypothesis was confirmed. Also, CSE and ESDE and CSDE explain 10.6% of ESE.

  • Hypothesis 2 (H2): ESDE has a positive and significant effect on ESE

    ISDE has a positive influence of 0.224 on ESE. The hypothesis was confirmed.

  • Hypothesis 3 (H3): ESE have a positive and significant effect GEI

    ESE has positive and significant of 0.705 on GEI. The hypothesis was confirmed.

    The complete model explains the 49.7% of GEI.

8 Discussion

It has been possible to show that the questionnaire met the reliability criteria through internal consistency (Cronbach’s alpha and composite reliability) and discriminant validity was met. Previously, [54] had confirmed by means of a study in 374 Chinese university students what has been corroborated in the present study: the effect of ESDE on ESE. This relationship was also previously verified in 560 university students in Lebanon by [42] and in 376 university students in Indonesia [61].

Through this study it is possible to demonstrate what is perceived from the student group regarding the entrepreneurial ecosystem in universities, that is, to be able to know if various contents are being reflected in the courses for the development of green enterprises. These efforts made by universities have already been reported by other institutions such as University of Melbourne [35] and Amsterdam Business School [52]. The fairs that allow showing the preliminary results of the undertakings, both of the students individually and organized with other students or even teachers, encourage the further development of green undertakings, especially when the issue of sustainability becomes an increasing need for business resilience and investments focused on the Sustainable Development Goals.

When correlational studies are developed, there is the great advantage of being able to show the prognoses of behavior that can occur in each population. Thus, when it is possible to demonstrate that the curricular components and, especially, the non-curricular ones, have a very relevant effect on self-efficacy and finally on GHG, investment plans can be generated to promote these activities that can be carried out independently different modes. Currently, the use of technologies to generate innovation in enterprises is being increasingly experimented with [2, 10, 26].

9 Conclusions

The study allows a contribution in the understanding of the influences of the variables in a university ecosystem that increasingly seeks to promote and carry out entrepreneurship. The positive and significant effects show that the model is valuable, on the one hand to understand reality and generate improvement plans in pursuit of more sustainable enterprises. On the other hand, it should be noted that the model may be used in future studies in other regions, which will serve to characterize these entrepreneurial ecosystems. Through the SEM-PLS analysis technique, it is possible to have a methodological strength; however, there are opportunities for future studies that can also use this methodology but are carried out through experimental design, which help to corroborate the relationships more reliably between variables and can describe reality more closely.