Factors Affecting Green Entrepreneurship Intentions in Business University Students in COVID-19 Pandemic Times: Case of Ecuador

This research assesses the influence of education development support, conceptual development support, and country support through entrepreneurial self-efficacy over green entrepreneurial intentions. A total of 532 business students in Ecuador participated in an online survey. Eight questions were focused on demographic information, and twenty-seven questions evaluated the green entrepreneurship intentions of students. An SEM-PLS technical analysis was used. The results showed that educational support for developing entrepreneurship (0.296), conceptual support for developing entrepreneurship (0.123), and country support for entrepreneurship (0.188) had a positive influence on entrepreneurial self-efficacy, and that entrepreneurial self-efficacy had a positive influence (0.855) on gren entrepreneurial intentions. The model explained 73.1% of the green entrepreneurial intentions. Outcomes of the bootstrapping test were used to evaluate if the path coefficients are significant. This study showed the impacts of education development support, conceptual development support, and country support on the entrepreneur’s ability to carry out green entrepreneurship were positive. This information can help universities develop strategic plans to achieve ecological ventures and ensure students have the necessary skills to do so on campus. The research findings also may be helpful for the governments in establishing new norms to promote entrepreneurship. The novelty is based on using the partial least square structural equation modeling (PLS-SEM) technique.

There are also studies available from Australia by Mitra [58], and from Africa, including Jesselyn and Mitchell in South Africa [59], Owusu-Mintah in Ghana [60], and Olokundun et al. [61]. In the case of the Americas, studies were reported from Canada by Chrisman, Hynes, and Fraser [62], the United States by Dill [63], Chile by Bernasconi [64] and Argentina by Postigo, and Tamborini [65]. Further, a critical study in entrepreneurship in some Latin American countries was carried out by Chafloque-Cespedes et al. [66]. Regarding green entrepreneurship, this subject was studied by Silajdžić, Kurtagić, and Vučijak in Bosnia and Herzegovina [67], Linskey in Japan [68], and Bonnet et al. in the Netherlands [69]. More recently, some investigations have identified different variables that have an influence of green entrepreneurship intentions [70].

Theory of Reasoned Action
The current study considers the theory of planned behavior (TPB) as a theoretical foundation to calculate the effect of contextual elements and self-efficacy on carrying out green entrepreneurship. Fishbein and Ajzen [71] proposed that TPB explains the factors that describe people's intentions behind the factors described by self-efficacy. Likewise, it includes intentions as a strong predictor of behavior. A country's laws or policies regarding green entrepreneurship intentions need to foster the self-efficacy to develop entrepreneurial activities.

Theory of Social Cognitive
Additionally, for this study, the theory of social cognitive developed by Bandura [72] is relevant, which emphasizes the belief that behaviors are within the individual's control and can augment self-efficacy. These aspects are reflected in the development of motivations to carry out entrepreneurial activities, educational supports for green entrepreneurship, and laws and policies that facilitate these undertakings.
Entrepreneurship orientation is a matter of constant evaluation in theoretical and practical research. Since Miller [73] began studying this variable, many investigations have been reported to understand the variables linked to this orientation and that ultimately impact the intention to carry out undertakings at different levels and of different types such as social or ecological entrepreneurship. Lumpkin and Dess [74] established in a general way that it has been possible to conceptualize the entrepreneurial orientation as the tendency towards decision-making that favors commercial activities' performance. The model of the present research also seeks to evaluate how the different types of support existing in the educational ecosystem as well as at the governmental level influence the entrepreneurial self-efficacy of students to increase the intention to develop green enterprises, which are less common.

Green Entrepreneurial Intention
The intention is the individual's state that creates decisions, attention, and interest to carry out a specific action [75][76][77]. Various factors affect the intention to act and directly affect the behavior. These can show how a person plans to carry out the linked behavior as indicated by the TPB [78]. The intention to perform a behavior precedes the behavior as such. There is evidence that entrepreneurship tends to positively influence entrepreneurship development [76,79,80]. Entrepreneurship is a concept that applies to both individuals and companies [73]. Green entrepreneurship involves additional concepts. Thus, we have the definition proposed by Farinelli [81], who states that green entrepreneurship is implementing innovations related to sustainability, with a focus on promoting the green economy among clients. Despite this intention of green entrepreneurship, entrepreneurs experience a problem establishing when an undertaking is green or not, so these undertakings are defined from the research results to facilitate their understanding. Thus, we can argue that green entrepreneurship involves addressing environmental issues and has a positive impact, such as the use of eco-friendly inputs, clean manufacturing processes, waste management, and recycling, among others. In other words, we not only talk about ecological entrepreneurship as a purpose of environmental care, but also approval of suppliers, purchase of materials, and clean processes. However, the definitions are likely to continue to be the subject of research and debate. In this study, we consider the intention of developing green entrepreneurship by university students.

Country Support for Entrepreneurship
This variable is understood as initiatives developed in a country to collaborate in ventures [82]. The variable allows descriptions of what the student thinks about the country's promotion and support activities for environmental and ecological ventures. Another factor measures if the student feels that the country offers options for developing ventures, which can be assessed as perceptions of easy to obtain bank loans for carrying out ventures. It is necessary to measure if country support influences self-efficacy for the development of ecological entrepreneurship. Therefore, the following hypothesis is formed: Hypothesis 1 (H1). Country support for entrepreneurship has a positive influence on entrepreneurial self-efficacy.

Educational Support for Developing Entrepreneurship
This construct is understood as universities' training activities to develop ventures [83]. The educational support focuses on offering compulsory subjects that describe how to develop ventures, including real projects to learn about the development of ventures; additionally, it focuses on offering pre-professional practice in firms focused on entrepreneurship orientation. This construct is also measured regarding whether conferences and academic workshops are held to develop competencies and obtain better knowledge about ventures, including linking students with successful entrepreneurs. It is essential to measure if education development support influences self-efficacy for the development of ecological entrepreneurship. For that, the following hypothesis is formed: Hypothesis 2 (H2). Educational support for developing entrepreneurship has a positive influence on entrepreneurial self-efficacy.

Conceptual Support for developing Entrepreneurship
This construct is understood as the university's efforts to provide technical knowledge about entrepreneurship and, in this way, contribute to awareness about entrepreneurship in students who can develop successful ventures, motivating students for the creation of new ventures [84]. Also included in this construct are generating new business ideas, both in the environmental and social fields, and considering a business approach. It is helpful to measure whether the conceptual development support influences self-efficacy for the development of ecological entrepreneurship. For that, the following hypothesis is formed:

Hypothesis 3 (H3).
Conceptual support for developing entrepreneurship has a positive influence on entrepreneurial self-efficacy.

Entrepreneurial Self-Efficacy
This variable is the belief that a person has about their ability to do any activity successfully and incorporate concrete behaviors into their daily agenda [85,86]. Entrepreneurial self-efficacy refers to the person's confidence in developing entrepreneurial activities and ultimately generating ventures [87,88]. Research evidence indicates the positive influence of entrepreneurial self-efficacy over entrepreneurial intention [89][90][91], which can be understood as people having a high level of self-efficacy, and is more likely to start ventures. The same applies to green businesses, which are of great importance in these times of COVID-19 [92]. For that, the following hypothesis is formed: Hypothesis 4 (H4). Entrepreneurial self-efficacy has a positive influence on green entrepreneurial intention. Figure 1 shows the research model detailing the relationship between the study variables. The model includes education development support, conceptual development support, and country support through entrepreneurial self-efficacy and green entrepreneurial intention. The circles represent each variable of the study, and the rectangular boxes indicate items for each variable.

Hypothesis 3 (H3).
Conceptual support for developing entrepreneurship has a positive influence on entrepreneurial self-efficacy.

Entrepreneurial Self-Efficacy
This variable is the belief that a person has about their ability to do any activity successfully and incorporate concrete behaviors into their daily agenda [85,86]. Entrepreneurial self-efficacy refers to the person's confidence in developing entrepreneurial activities and ultimately generating ventures [87,88]. Research evidence indicates the positive influence of entrepreneurial self-efficacy over entrepreneurial intention [89][90][91], which can be understood as people having a high level of self-efficacy, and is more likely to start ventures. The same applies to green businesses, which are of great importance in these times of COVID-19 [92]. For that, the following hypothesis is formed: Hypothesis 4 (H4). Entrepreneurial self-efficacy has a positive influence on green entrepreneurial intention. Figure 1 shows the research model detailing the relationship between the study variables. The model includes education development support, conceptual development support, and country support through entrepreneurial self-efficacy and green entrepreneurial intention. The circles represent each variable of the study, and the rectangular boxes indicate items for each variable.

Methodology
The methodology used in the current study includes an observational study with both descriptive and inferential design. The aim is to identify and describe the factors that can explain the intention of green entrepreneurship.

Sample
The study involved business university students from Ecuador. As inclusion criteria, business students from universities in Ecuador and 18 years and older were considered. As exclusion criteria, students in the first year were not considered. The sample consists of 532 participants, 199 men (37.4%) and 323 women (62.6%), ranging between 18 and 29 years. The average age was 22.6, with a standard deviation of 2.9 years.

Methodology
The methodology used in the current study includes an observational study with both descriptive and inferential design. The aim is to identify and describe the factors that can explain the intention of green entrepreneurship.

Sample
The study involved business university students from Ecuador. As inclusion criteria, business students from universities in Ecuador and 18 years and older were considered. As exclusion criteria, students in the first year were not considered. The sample consists of 532 participants, 199 men (37.4%) and 323 women (62.6%), ranging between 18 and 29 years. The average age was 22.6, with a standard deviation of 2.9 years.

Data Collection and Instrument
The data collection used a questionnaire in Google Forms, which was run online 10 to 15 February 2021. The data collection using the online questionnaire was distributed to business university students by email and personal chats. For ethical purposes, the questionnaire was applied to students who agreed to participate after reading the statement, "your participation is voluntary; therefore, the information obtained will be confidential and will only be used for research purposes".
The questionnaire used has two sections. The first collects sociodemographic data from the business university students. The second section includes original questions and questions based on other instruments in the following areas: education development Sustainability 2021, 13, 6447 6 of 16 support [93], conceptual development support [93], country support (current authors), entrepreneurial self-efficacy [94], and green entrepreneurial intention [93,95,96]. The original items were translated and adapted linguistically. The variables are measured using a 5-point Likert-type scale (where 1 = completely disagree, to 5 = completely agree). The scale of education development support consists of six items, conceptual development support four items, country support four items, entrepreneurial self-efficacy four items, and entrepreneurial intention eight items. The first version of the online questionnaire was checked by sustainability and entrepreneurship experts. The final version of the questionnaire was uploaded in Google Forms. The students completed the online form anonymously. At the beginning of the questionnaire, students were informed of the aim of the research, and informed consent was obtained.

Data Analysis
To evaluate the data collected, SPSS version 26 and SmartPLS version 3.3.2 were employed. Sometimes doubts arise about the need to compare between using PLS-SEM and covariance-based structural equation modeling (CB-SEM), but it is important to understand that they are complementary methods [97]. PLS-SEM does not seek to mimic CB-SEM [98,99]. The following is recommended [100]: a. If the objective is predicting key target constructs or identifying key 'driver' constructs, select PLS-SEM. b. If the goal is theory evaluation, confirmation of a theory, or comparison of two or more theories, select CB-SEM. c. If the study is exploratory or an extension of an existing structural theory, select PLS-SEM.
Additionally, Rigdon et al. [100] and Sarstedt et al. [101] identified differences regarding when to use PLS-SEM and CB-SEM.
PLS-SEM must be used when: a. The objective is predicting key target constructs or identifying key "driver" constructs. b. The structural model is complex (some constructs and some indicators). c. The plan is to use construct scores in subsequent analyses.
CB-SEM must be used when: a. The objective is theory evaluation, theory confirmation, or the comparison of different theories. b. The structural model has circular relationships. c. The study needs a global goodness-of-fit criterion.
Likewise, SEM PLS is used for samples that do not have a normal distribution and require a non-parametric analysis, as does the current study. Further, SEM PLS delivers the R2 values and, at the same time, indicates the significance of relationships between constructs to demonstrate how well the model is performing. In the case of CB-SEM, only path modeling is provided. Finally, SEM PLS can handle many independent variables simultaneously [102]. All these reasons explain and support the choice to use PLS-SEM for the current study. The internal consistency of each subscale was analyzed using Cronbach's alpha reliability coefficient, construct and discriminant validity, and internal consistency through composite reliability [97]. The reliability of each indicator is evaluated by measuring the indicator's loads and their dimensions. The average extracted variance is utilized to analyze the fit of the model. In addition, the Fornell-Larcker criterion [98,99] is used to evaluate the discriminant validity.

Reliability
The reliability of scales obtained by analysis of internal consistency is listed in Table 1. The variables' scales showed reliability coefficients (Cronbach's Alpha) higher than the expected minimum of 0.5 in the exploratory analysis (see Table 1).

Validation with SEM-PLS
The instrument's validation by SEM-PLS includes a reliability analysis of each item, the internal consistency of dimensions using composite reliability, analysis of the average variance extracted, and discriminant validity. An acceptable value of composite reliability is more significant than 0.707. The coefficients of reliability composed of each instrument's sub-scales were between 0.555 and 0.943 (see Table 2). Values obtained in the sub-scales are observed to confirm the reliability of the instrument.

Discriminant Validity Using SEM-PLS
Discriminant validity was calculated using the Fornell-Larcker criterion [98], as shown in Table 3. To do this, in the first column, the square root of the extracted variance that appears in the upper part in parentheses must be greater than the correlations that appear in the same column in the following lines of the same column. This criterion is applied for each column. Table 3 shows the fulfillment of this criterion in all the subscales, demonstrating the discriminant validity of the tested instrument. Conceptual support for developing entrepreneurship: CSDE; Country support for entrepreneurship: CSE; Educational support for developing entrepreneurship: ESDE; Entrepreneurial self-efficacy: ESE; Green entrepreneurial intention: GEI.

Bootstrapping
The Bootstrapping Technique is a non-parametric procedure used to evaluate if the path coefficients (beta) are significant [100]. Bootstrapping is a statistical technique for estimating quantities over a population by averaging estimates from multiple small data samples. Samples are constructed by extracting observations from a large data sample one at a time and returning them to the data sample after they have been chosen, which allows a given observation to be included in a given small sample more than once. This sampling approach is called replacement sampling. In order to efficiently calculate if the tested model is significant, the calculation is carried out, indicating in the software that it is to be carried out 5000 times. It is seen in Table 4 that three values are significant (p values < 0.01). Conceptual support for developing entrepreneurship: CSDE; Country support for entrepreneurship: CSE; Educational support for developing entrepreneurship: ESDE; Entrepreneurial self-efficacy: ESE; Green entrepreneurial intention: GEI. Figure 2 shows the research model tested. The results confirm that education development support, conceptual development support, and country support through self-efficacy influence green entrepreneurship intention in business students.  Conceptual support for developing entrepreneurship: CSDE; Country support for entrepreneurship: CSE; Educational support for developing entrepreneurship: ESDE; Entrepreneurial self-efficacy: ESE; Green entrepreneurial intention: GEI Figure 2 shows the research model tested. The results confirm that education development support, conceptual development support, and country support through self-efficacy influence green entrepreneurship intention in business students.

Hypothesis 1 (H1). Country support for entrepreneurship has a positive influence on Entrepreneurial self-efficacy
Country support has a positive influence of 0.188 over Entrepreneurial self-efficacy. The hypothesis was confirmed. Country support and educational support for developing entrepreneurship and Conceptual support for developing entrepreneurship explain 27.3% of Entrepreneurial self-efficacy.

Hypothesis 2 (H2). Educational support for developing entrepreneurship has a positive influence on Entrepreneurial self-efficacy.
Educational support for developing entrepreneurship has a positive influence of 0.296 over Entrepreneurial self-efficacy. The hypothesis was confirmed.

Hypothesis 3 (H3).
Conceptual support for developing entrepreneurship has a positive influence on Entrepreneurial self-efficacy.  Hypothesis 1 (H1). Country support for entrepreneurship has a positive influence on Entrepreneurial self-efficacy.

Test of Hypothesis
Country support has a positive influence of 0.188 over Entrepreneurial self-efficacy. The hypothesis was confirmed. Country support and educational support for developing entrepreneurship and Conceptual support for developing entrepreneurship explain 27.3% of Entrepreneurial self-efficacy.

Hypothesis 2 (H2).
Educational support for developing entrepreneurship has a positive influence on Entrepreneurial self-efficacy.
Educational support for developing entrepreneurship has a positive influence of 0.296 over Entrepreneurial self-efficacy. The hypothesis was confirmed.

Hypothesis 3 (H3).
Conceptual support for developing entrepreneurship has a positive influence on Entrepreneurial self-efficacy.
Conceptual development support has a positive influence of 0.123 over Entrepreneurial self-efficacy. The hypothesis was confirmed.

Hypothesis 4 (H4). Entrepreneurial self-efficacy influences Green entrepreneurship intention.
Entrepreneurial self-efficacy has a positive influence of 0.855 over Green entrepreneurship intention. The hypothesis was confirmed.
The complete model explains the 73.1% of Green entrepreneurship intention.

Discussion
The current study's objective is to evaluate the influence of educational support for developing entrepreneurship, conceptual support for developing entrepreneurship, and country support for entrepreneurship through entrepreneurial self-efficacy over green entrepreneurial intention in business students in Ecuador. We ensured that the questionnaire could be trusted, calculating the discriminant validity and reliability (internal consistency-Cronbach's alpha coefficient and composite reliability). The outcomes obtained showed that the instrument was valid, reliable, and statistically relevant in applying the sample and can show if the model explains the factors that describe green entrepreneurship intention.
The influence of education development support on entrepreneurial self-efficacy verified in the present study is similar to that reported by Shi et al. [101] for 374 Chinese university students. Likewise, this relationship could be verified in the study of Mozahem and Adlouni [102] for 560 university students from Lebanon, and the results coincide with the findings for 376 university students in Indonesia [103]. It is relevant to know if universities are offering careers focused on entrepreneurship or offering postgraduate programs in entrepreneurship such, as is done at the University of Melbourne [104] and Amsterdam Business School [105]. It is also relevant to confirm that universities benefit from organizing conferences on entrepreneurship since the preliminary results of entrepreneurship efforts can be disseminated and generate contact with successful entrepreneurs, who can relate their experiences and motivate students to undertake entrepreneurship.
The influence of conceptual development support on entrepreneurial self-efficacy verified in the present study is similar to that reported by Burnette et al., who conducted a study in the USA on 238 undergraduate students [106]; likewise, the result identified here coincides with that found in a study of 109 undergraduate university students from South Africa [107], as well as with the results reported by Cadenas [108] in the USA, Shi et al. [101] in China, and Elnadi and Gheith [109] in Saudi Arabia. It is essential to know if a university has focused on creating awareness about entrepreneurship by influencing so that students at the end of their studies can choose entrepreneurship as a professional career. Similarly, the motivation that students may have to start a new business is valued. Among the most significant aspects is knowledge of whether the university provides in an organized and systematic way ideas to generate new businesses based on entrepreneurship. In this sense, it is important that future researchers specifically ask whether universities have think-tanks, such as those at the University of Oxford [110] and Harvard University [111].
The influence of country support on entrepreneurial self-efficacy verified in the present study is similar to that reported by Memon, et al. [112], who evaluated 564 university students from Pakistan. Similar results were found in the study by Nowiński, et al. [113], who evaluated 360 university students in the USA and 1054 university students in Poland. When entrepreneurship is evaluated, the question has usually been evaluated of whether institutional support is received. However, very rarely is the support given by governments for ecological entrepreneurship evaluated. Therefore, it is helpful to evaluate this support from the country, which also has to modify specific laws and move the state and the banks to promote investment in green enterprises, with guaranteed loans at reasonable rates so as to encourage new green entrepreneurs. Country support for entrepreneurship together with educational support for developing entrepreneurship and conceptual support for developing entrepreneurship explains 17% of self-efficacy.
The relation between the variables is very relevant since it allows us to understand how the influences between the variables discussed in the current study can make students feel that they can carry out green ventures based on the knowledge obtained. The skills developed due to supports provided through courses, practices, and the country's regulatory framework. These aspects build confidence in students to develop green ventures that also contribute to the SDGs.
The influence of self-efficacy on green entrepreneurship intention demonstrated in the present study is similar to that reported by Soomro et al. [114] in a study of 284 university students from Pakistan. Little research has been carried out specifically on ecological entrepreneurship intention, so this study provides a reference for Latin America. There is significant growth in entrepreneurship, providing an excellent opportunity to implement green entrepreneurship, with a corresponding impact on the environment.

Conclusions
The current study's main contribution is to understand the variables that affect entrepreneurship intention. It has been found that the three variables described have a relevant impact on the self-efficacy variable, which is the last variable for the intention of developing ecological enterprises. As the literature is limited to green enterprises, this study seeks to broaden that thematic interest. The analysis technique employed is a strength of this article, as it has permitted correlations to be detected between the same variables using multivariate analysis by modeling structural equations using partial least squares (SEM PLS).
This study could be reproduced in other cities or regions, e.g., Latin America or Europe. However, we need to evaluate each case in detail because each country has its own entrepreneurship efforts, different government rules, and university governance. It has also been possible to develop an instrument that can be applied in future research and refined for further research.

Theoretical Implications
The development of green entrepreneurship and related research is still limited in the academic literature, and little is known about the factors that affect student intentions regarding green entrepreneurship. As a novel feature, we have incorporated into the model the support that students feel internally and externally. Internal support is evaluated from the training courses and the promotion of events, approach to entrepreneurs, and even financing to start ventures. From the external side, government support is evaluated from normative aspects or direct or training support. It is expected that the results for each country may be somewhat different, considering that supports differ from governments and even universities, but are still part of the model of internal-external influences. When using SEM PLS, it has been possible to achieve results that measure both the correlation between variables and the pathway to explain green entrepreneurship.

Practical Implications
In the annual programming in universities, action plans are developed in which it is expected that increasing motivations toward green entrepreneurship will be incorporated. The findings can draw the attention of universities so that they can better know the factors that students see as important and so that they can request from the institutions through changes in the content of courses and development funds to support green enterprises. The utilization by universities of green entrepreneurship content to attract future students is an opportunity not widely used by these institutions.
The future development of green entrepreneurship must be precisely evaluated to know what factors influence it and to recognize what changes are being made by the authorities in universities to increase the development of green entrepreneurship by students. The government can evaluate these changes. Green entrepreneurship is likely to continue to grow and will require additional evaluations in different populations. Institutional Review Board Statement: Ethical review and approval were waived for this study because it does not involve any risk to the participant's life or health. No substance has been tested on the participants or put them in danger at any time.
Informed Consent Statement: Patient consent was waived because it would not be part of any medical intervention and no drug substance was to be tested.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author.

Conflicts of Interest:
The authors declare no conflict of interest.

Ethical Approval & Informed Consent:
All procedures performed in studies involving human participants were by the ethical standards with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.