Factors Influencing Entrepreneurial Intention among Agricultural Engineering Students in Adverse Business Environment (2024)

1Entrepreneurship is recognized as a powerful engine for economic development (Dhaliwal, 2016). In addition to creating jobs, innovative new businesses foster economic growth (Shane & Venkataraman, 2000). For this reason, leading scholars have called for more entrepreneurship and more entrepreneurial activities (York & Venkataraman, 2010), particularly among young and educated people. Entrepreneurial intention among the latter is an important step toward new business creation (Belchior & Lyons, 2021).

2Entrepreneurial intention (EI) has received important scientific attention over the last two decades (Belchior & Lyons, 2021; Koe et al., 2012; Liñán & Fayolle, 2015). Most of the studies were conducted in developed countries. In the recent years, an emerging literature was focusing in the developing world (Al-Qadasi et al., 2023). From Shapero & Sokol (1982) theory of the entrepreneurial event, and Ajzen (1991) theory of planned behavior, to Davidsson (1995) economic-psychological model, there is an established literature on factors affecting EI. Lüthje and Franke (2003) structural model of EI completed the previous literature by taking into account contextual variables, to model students’ IE. This effort which has been well accepted by other scholars (Al-Qadasi et al., 2021, 2023; Liñán & Fayolle, 2015) is appropriate to study EI in developing countries where the context may be adverse (Paul et al., 2021).

3In this regard, the case of Haiti is emblematic. People in this country are the poorest in the western hemisphere. Previous research has argued that Haitian context is an adverse business environment (Paul et al., 2021). However, no research has focused on EI in Haiti. More widely, few if any research on EI focused on agricultural engineering students, and none were conducted in a particular adverse business environment like Haiti.

4Entrepreneurship education initiative started only after the 2010 earthquake in Haiti (Paul et al., 2021) and sociopolitical crises affected negatively the economic situation. Since 2019, Haiti is experiencing negative economic growth. From this year of political unrest to 2022, the economic growth rate was respectively -1.7% in 2019; -3.3% in 2020, -1.8% in 2021, and -1.7% in 2022 (IHSI, 2022). This economic recession (with an average of -2.1% growth rate for the last 4 years) was worsened by the COVID-19 and the acute political crisis which culminated in the magnicide of the president in July 2021. An important part of the young and educated people is attracted by selective migration policies in the Western world. During these turbulent times, data collected by the Americas Barometer revealed a particularly high intention for migration among the Haitian population, 74% of all Haitians were likely to emigrate in 2021, particularly to the United States of America (Gélineau et al., 2021). This migration intention was even higher among the youth community (81% for the 18-25 years old) which represents more than 20% of the almost 12 billion people living in the western part of Haiti Island (UNFPA, 2016).

5In this context, Haitian government failed to create economic stability, food security, and job opportunities undermines the achievement of the engagement for the Sustainable Development Goals (SDGs). Recently, for the first time, Haiti was listed among the top 7 countries stressed by severe food insecurity (FSIN, 2023), in addition to other forms of insecurity.

6In this critical socioeconomic environment, what is often sketched about Haiti is its world highest rate of migration of skilled people (Jadotte, 2012). However, creating their own jobs represents a desirable choice for many young and skilled people, even in an informal economic approach, and one of the naturally appropriate sectors to create revenue in Haiti is agriculture which is already one of the most important fields of economic occupation in the country.

7This research focused on agricultural university students' entrepreneurial intention and contributes to fill the above gap. It uses empirical data from a country-representative survey conducted in 2022 among a sample of agricultural engineering students in Haiti, to answer the following research questions: What is the entrepreneurial intention prevalence rate among students in agricultural engineering schools in Haiti? What are the determinants of this intention?

8Through statistical and econometric analysis, we test the following hypotheses:

• H1) Despite the risky agricultural sector and the adverse business environment of Haiti, students in agricultural engineering schools express a high entrepreneurial intention prevalence rate.

• H2) Students' entrepreneurial intention is determined by their knowledge in business, knowledge in the agricultural sector and their entrepreneurial personality traits.

9Research findings from empirical test of these hypotheses can help decision makers in developing countries like Haiti to better address entrepreneurship development among young people.

11. Theoretical foundation of entrepreneurial intention

10Entrepreneurial intention is defined as the “temporal cognitive state and causally precedes entrepreneurial action” (Krueger, 2017). In social sciences, intention models and theories focusing on consumption and entrepreneurship have been developed and used for decades. The intention is an entire stage of a final consummatory intentional action (Lewin, 1951). It is the conscious plan to perform a given behavior (Livingston, 2005).

11Literature on entrepreneurial intention shows robust debate among four major theories (Al-Qadasi et al., 2023). They are respectively theory of the entrepreneurial event proposed by Shapero and Sokol (1982), theory of planned behavior pioneered by Ajzen (1991), economic-psychological model by Davidsson (1995), and Lüthje and Franke (2003) model.

12Shapero and Sokol (1982) were the first to propose an entrepreneurial intention model. This model inspired the theory of planned behavior (Ajzen, 1991) which was built upon works started by Fishbein (1963). Fishbein (1967), and Ajzen and Fishbein (1973) have continuously updated such studies. An updated version of this model was developed by Krueger and Carsrud (1993), which he kept developing according to significant changes in social life. For Krueger et al. (2000), identifying opportunities is clearly an intentional process. According to them, threats, weaknesses, and strengths must be addressed in any opportunity quest. By comparison, they may be the attitude toward behavior, perceived norms, perceived behavioral control, or actual control (Fishbein & Ajzen, 2011; Nguyen, 2012). Therefore, internal and external factors could positively or negatively affect entrepreneurial intention among agricultural engineering students.

13The entrepreneurial event theory suggests three main factors that could affect an individual’s decision to start a new business: perceived desirability, perceived feasibility, and propensity to act upon opportunities (Krueger Jr et al., 2000). Perceived desirability measures how attractive is starting a new business to the individual. Perceived feasibility measures an individual’s perception of his ability to start a business. The propensity to act is “the personal disposition to act on one’s decisions” (Krueger Jr et al., 2000).

14The theory of planned behavior (TPB) assumes that three attitudinal factors determine an individual’s entrepreneurial intention and behavior: the subjective norm, perceived behavioral control, and attitude toward the behavior (Ajzen, 1991). Attitude toward the behavior describes how individuals anticipate the performance of a specific behavior either positively or negatively (Utami et al., 2018). Subjective norms reflect the effect of the social groups on the decision of an individual to perform or not perform a particular behavior or action (Ham et al., 2015). The perceived behavioral control is related to an individual’s belief on his ability to start a new business.

15The economic-psychological model developed by Davidsson (1995) contributes to understand the role of an individual’s conviction as the primary determinant of EI. The model helps to test the effect of economic and psychological factors that influence individuals’ intentions to go into business for themselves. Davidsson (1995) argued that this conviction is based on (i) general attitudes (need to change, achievement, autonomy, competitiveness, and money orientation), (ii) domain attitudes (payoff, social contribution, and know-how), and (iii) the current situation (current employment status). Davidsson (1995) connects conviction, intention and situation.

16The fourth model proposed by Lüthje and Franke (2003) combined two factors, personality traits and contextual variables, to model students’ EI. Through that model, the authors suggested that personal traits are at the basis of individual attitude, and contextual variables refer to environmental factors that could support or undermine EI . The Lüthje and Franke Model (LFM) is used by other researchers to investigate the personal and environmental determinants of EI (Al-Qadasi et al., 2021, 2023; Kristiansen & Indarti, 2004; Schwarz et al., 2009). And, according to Liñán and Fayolle (2015) there is still more research to be done to understand better how the context affects EI. This is even more important in context of risky and adverse business environment discussed below in the particular case of Haiti.

1.2. Determinants of entrepreneurial intention

17The above theories provide a range of determinants of entrepreneurial intention. Al-Qadasi et al. (2021) tested an integrated EI model that combined TPB personality factors and LFM contextual factors. In a recent study, Al-Qadasi et al. (2023) tested critical environmental factors, namely entrepreneurial finance, entrepreneurial social networks, and availability of business information. For example, Nowiński & Haddoud (2019) showed that existing role inspiring entrepreneur role model was not a predictor of EI.

18Personality traits are considered closely related to EI because they affect individual's need and motivation (López-Núñez et al., 2022). They also include socio-demographic characteristics (Cassol et al., 2022; Rusu et al., 2022; Zakaria et al., 2014). Many studies on personality traits concentrated mainly on three traits: need for achievement, locus of control, and entrepreneurial self-efficacy (Al-Qadasi et al., 2023; Karabulut, 2016; Nasip et al., 2017; Uysal et al., 2022).

19Situational factors have been identified either as motivating factors (Shapero & Sokol, 1982) or obstacles (Arrighetti et al., 2016) to entrepreneurship intention. Al-Qadasi et al. (2023) also found that economic-political instability condition, instead of harming Yemen students’ intentions to become future entrepreneurs, have motivated their EI.

20Concerning entrepreneurial education, results of survey in Turkey showed that educational and structural support factors affect the entrepreneurial intention of students (Turker & Sonmez Selcuk, 2009). Paul et al. (2021) have suggested that knowledge in business plan could influence students’ decision to create business.

1.3. Entrepreneurial intention in context of risky and adverse business environment

21Entrepreneurship is linked with both risk and opportunity. Entrepreneurial activities are more challenging in risky and adverse business environments. Countries in crises like Haiti are even more challenging for the expression of entrepreneurial intention. However, there is a growing interest to investigate entrepreneurial intention in times of crisis which can create or worsen risky and adverse business environment. In the case of developed countries, Arrighetti et al. (2016) surveyed 3,684 Italian University students enrolled in 12 different faculties to investigate the impact of a prolonged economic recession on the entrepreneurial intentions of young people. The study found that while the perception of the economic crisis as an obstacle to new business creation did not impact on the propensity toward entrepreneurship, it had a negative and highly significant impact on the likelihood to start a business.

22Conversely, in developing countries like Yemen, Al-Qadasi et al. (2023) collected data among 487 final-year university students from two universities (public and private) in Yemen, one of the poorest Arab countries with numerous economic and political challenges. The study focused on the factors influencing entrepreneurial intention. The results revealed that personality traits of the need for achievement and locus of control positively correlated with entrepreneurial self-efficacy and entrepreneurial intention. Despite a challenging crisis since 2011, the study found that even a context of war has not discouraged Yemen students’ intentions to become future entrepreneurs.

23In Latin America, Bustamente et al. (2020) explored the moderating effect of a natural disaster on the well-studied relationship between entrepreneurship-oriented beliefs (behavioral, normative, and control beliefs) and entrepreneurial intentions. The study used data from the Global Entrepreneurship Monitor before and after the earthquake that took place in Chile on February 27, 2010. The study was performed by applying a multilevel hierarchical logit regression over a sample of 14,724 individuals from the six most affected regions. The results indicated that natural disasters shape the relationship between entrepreneurial intentions and all its three motivational antecedents. They suggested that the earthquake strengthened the relationship between entrepreneurial attitudes and entrepreneurial intentions. Furthermore, the authors found that the earthquake had a positive effect on the relationship between perceived behavioral control and entrepreneurial intentions.

24Similarly, the case of Haiti offers an appropriate context to study entrepreneurial intention in times of crisis. Haiti is characterized by chronic crisis. In January 2010, the country was hit by a deadly earthquake that destroyed the metropolitan area. After a short pause, in 2016, a violent hurricane devastated the southwestern part of the country. A sociopolitical crisis took place since the election of 2016-2017 and peaked in 2018-2019. In July 2021, the president in service was assassinated, one month before the southwest was hit by a new earthquake. In the meanwhile, armed groups occupied about 80% of the metropolitan area creating a difficult context for socioeconomic activities because of these multiple crises (Paul et al., 2022). These included continuous socio-political instability, low economic growth, and recurrent natural disasters.

25In terms of socio-political and financial environment, since 1989 Haiti has been facing amplifying political instability (Wah, 2013). The Governments are weak (Lena, 2022), and this weakness affects the social condition of the population, specifically in terms of security. On the one hand, the current situation is risky in terms of protection for personal properties, businesses, and even human life (Lemay-Hébert, 2018). On the other hand, access to credit is so restrictive in Haiti (Sifrain, 2022) that investment is limited in all the economic sectors. This situation leads to the business community’s negative perception of the banking sector regarding their contribution to economic development in Haiti (Paul et al., 2020). Mombeuil (2020) argues that Haiti’s elites are willing to maintain the status quo of the chaotic socioeconomic and institutional conditions. The low investment would imply a lack of large businesses, particularly in the agricultural sector (Bélizaire & Lea, 1993). Therefore, finding a job after graduation in Haiti becomes very competitive (Roberts et al., 2019). Existing data shows that nearly half of the active of 20–24 years, and almost four active aged 25–29 in ten are unemployed and 50% of the unemployed are under 30 years (IHSI, 2012).

26In such a context, using entrepreneurship to enable youth to create their own businesses (as argued by Premand et al. (2016)) has been considered one of the best alternatives. After the 2010 earthquake, entrepreneurship was largely promoted in Haiti. But much of the entrepreneurship programs ended before 2020. Impact studies showed interesting but limited consequences (Paul et al., 2021), and the people's intention turned toward migration (Gélineau et al., 2021).

27The Haiti’s existing entrepreneurship context is marked by individual informal microbusinesses. More than 80% of the existing businesses had no legal status, according to a census led by the Ministry of Commerce and Industry (MCI, 2014). In addition, farmers (one million according to the Ministry of agriculture) were not included in this census, since they were not considered as entrepreneurs. However, the agricultural sector offers several advantages in terms of innovation and entrepreneurship opportunities, despite challenges in terms of risks. Haiti has an existing and growing demand for agri-food products(Celestin, 2019). Vansteenkiste (2017) argued that Haitian agribusiness could produce its imported goods. And Paul (2016) demonstrated that entrepreneurship can help creating growth in the agriculture.

28In terms of opportunities, Haitian agribusiness can access a broader market among the members of the Caribbean Community and Common Market (CARICOM) (Lewis, 2022). Despite frequent natural disasters that create risks for agribusiness development (Elusma et al., 2022), analysts supported that managing these hazardous events guaranteed a long-lasting life for several agribusiness companies in Haiti (Bélizaire & Lea, 1993). Because of its climate, Haiti enjoys distinctive advantages over other countries in the region in producing many products including mangoes, coffee, sorghum, and sugar cane (Gabriel, 2018).

29The above context justifies the present study on entrepreneurial intention. Studying factors influencing entrepreneurial intention is particularly important in risky context (Bustamante et al., 2020). To our best knowledge, this is the first study to focus on entrepreneurial intention and target agricultural engineering students.

2.1. Model

30In addition to statistical analysis, we studied the entrepreneurial intention by estimating a probabilistic model. We consider a student i (where i=1, 2…I) earns a utility for having and therefore expressing a positive entrepreneurial intention (EI). This utility is not observable; it is a latent variable. However, it determines the choice for expressing EI. We assume that a student i expresses a positive entrepreneurial intention if his/her utility for being a future entrepreneur is superior to a threshold , whereas he/she expresses a negative or low entrepreneurial intention if his/her utility is inferior or equal to this threshold. The Utility function U_i^* may be explained by a deterministic part which is a vector of observable characteristics and an error term (ɛ_i). For the student i this utility function can be written as follows:

31The error term is supposed to be independent and identically distributed, as follows: ε_i~N(0,1). The rule of decision, for each student i, is to make the choice that maximizes his/her utility function. To study the personal characteristics of the students that explain their choice, we first define a binary variable y_i that measures their choice, as follow:

32Although the utility of an entrepreneurial intention is not observable, this is not the case for the choice of a student. We can observe the choice of the student after he/she expressed his/her entrepreneurial intention. This choice, measured by y_i, as defined below, cannot be estimated by a linear model, since this endogenous variable can have only two values: 0 or 1. The variable Y_i takes the value 1, if the student has an entrepreneurial intention and 0 if not. In this case, the endogenous variable of the model is dichotomous. The linear multiple regression standard models can be written as suggested by Shin (1978) and Benoit (2011):

33Estimate this binary model implies to be certain that the predictions will fall into the interval (0, 1). And, as the number of observations (281) is sufficiently high, we confidently assumed that the data were distributed normally; which allows us to opt for a Logit model. The form of the equation to be estimated is then:

34In this relation, F is a cumulative density function given by

35The parameters 𝑚 and β of the model were estimated using
numerical maximization methods of the logarithm of the likelihood function
which is written as follows

36The vector of explanatory variables includes characteristics related to participants’ profile. The latest included the following demographic characteristics: search for autonomy, family entrepreneurial background, knowledge in business plan preparation, experience in leadership, identification of successful agribusiness. In our sample, age, gender, and education were not discriminant variables, since all the participants were at the university-level. Contrariwise, not all of them had previous knowledge in entrepreneurship. An environmental variable was selected in order to capture the contextual feature: entrepreneurship network. The awareness of the contextual risks was already included in the weighted intention.

2.2. Participants

37The present study included 281 students from a large range of agricultural engineering schools throughout Haiti. The ministry of education and vocational training officially recognized 21 agricultural schools, while it acknowledges the existence of certain additional unrecognized ones in the country. Our sample covered more than 25 agricultural schools, all the ten geographic departments and different categories of schools.

38Of these participants, 62.6% were enrolled in public schools and 37.4% in private ones. Out of the total number of students, 71.5% of them were male. Regarding the existence of business in their immediate environment, only 53.7% of them have some networking with enterprises, and 42.3% had at least one parent or some other family member performing entrepreneurial activities. A significant percentage (37.7%) of respondents stated they have work experience, however, a high percentage of 91.1 mentioned having occupied a youth leadership position in the past.

2.3. Instrument

39Data for this research were collected using an online Google form questionnaire from October 8th to December 15th of 2022. The questionnaire was sent through the faculty deans, professors, student committees, and directly to students from agricultural sciences in Haiti. From a total of 302 questionnaires filled out and returned, 281 were selected as accurate for this study. Different questions were asked on demographic, socioeconomic, entrepreneurial traits and perception of risk. Participants were also asked about their entrepreneurial intentions (‘Would you like to become an entrepreneur in the future?’). They had to answer yes or no. For other questions, they had to select from a Likert scale. SPSS was used for data processing and analysis. The following Table 1 presents the description of the variables used in the study.

Table 1. Variables description

2.4. Data Analysis

40Conducted on agricultural engineering students, the intention was not considered as a simple yes or no answer. The affirmation was weighted using three key entrepreneurship indicators (entrepreneurial context multiplicator) while focusing on the Haitian adverse business environment. A student who deliberately looks for knowledge and skills about doing business is somehow considered to be truly intentional about becoming an agricultural entrepreneur. Furthermore, the entrepreneurial intention is confirmed by the student’s awareness of the risky business environment of Haiti. It is therefore a weighted average of the research for knowledge and skills, self-perception of a risk-taking attitude, and optimism in managing the current risks of Haiti. Research of knowledge and skills is a dummy variable that indicates whether a student has decided by himself to follow some training on entrepreneurship besides his regular courses. Self-perception of risk-taking attitude is from a 5 points Likert scale question type, where each student esteems their risk appetite. And, optimism on managing the current risks in Haiti is a dummy variable revealing if a student is pessimistic or optimistic about the possibility of managing the risk. In the context of Haiti, this approach is justified by the fact that the entrepreneurial intention which can be transformed into effective business creation needs to be grounded in risk awareness.

41Answers from Likert scales such as Job expectation, resources availability, and Quest for Autonomy were categorized (low=0, high=1) for the analysis. As for the weighted entrepreneurial intention, it was scaled from zero to five and then transformed into binary variable according to the same consideration. We used the t-test, the ANOVA, and the Binary Logistic Regression as statistics for hypothesis testing and model estimation.

3.1. Prevalence of entrepreneurial intention among Haitian agricultural engineering students

42The survey revealed that 98.6 % of the students answered affirmatively (Yes) to the question, «Would you like to become an entrepreneur in the future? ». This is quite a very high percentage. However, when weighing the intention using the entrepreneurial consciousness of risk (based on risk awareness), we found that 54.1% had a conscientious intention to become an entrepreneur. This result confirms the first hypothesis that in the Haitian risky agricultural sector and adverse business environment, students in agricultural engineering schools express (and therefore have) high entrepreneurial intention.

3.2. Factors influencing entrepreneurial intention among Haitian agricultural engineering students

43Bivariate analysis (Table 2) revealed that student's entrepreneurial intention was not significantly different in terms of demographic characteristics (age, gender), the type of university, the community-based characteristics (family background in entrepreneurship) or available resource. The fact that a student was trained in entrepreneurship or had a business idea was not what strongly differentiating criteria for his/her EI. The search for autonomy, the possession of role models and knowledge in business plan preparation were the most important factors associated with students’ EI.

Table 2. Students’ EI by socioeconomic and demographic characteristics

Significance threshold: * significant at 10%, ** significant at 5%, *** significant at 1%, and ns not significant

44Based on the three major determinants often discussed in the theory of planned behavior, the results show that unlike attitude toward behavior, subjective norms and perceived behavioral control appear to have a good association with entrepreneurial intention, as shown in Table 3.

Table 3. Students’ EI determinants according to the theory of planned behavior

45The table 4 below displays the estimates, adopting backward variable selection in order to get the best specification. Non-significant variables (in Table 2) were not included in the regression.

Table 4. Logistic regression estimates for EI by students’ characteristics

Significance threshold: * significant at 10%, ** significant at 5%, et *** significant at 1%, and ns not significant

46The quality of the model is pretty acceptable. The likelihood ratio test is acceptable at 5%. Also, the prediction capacity of the model is 72.2%, and the error is normally distributed (Chi-2 test: 53.948 with a p-value of 0.000).

47The results of the study revealed that, despite an adverse business environment and high population intention to migrate, the prevalence of entrepreneurial intention among Haitian agricultural engineering students was high. This result confirms previous discussion on context of crisis and entrepreneurial intention(Al-Qadasi et al., 2023).

48Our findings from the link between students’ EI and the three traditional attitudes towards entrepreneurship are consistent with those observed in Chile after a natural disaster by Bustamante et al. (2020).

49The results also show that students' EI was determined by four characteristics: their search for autonomy, their knowledge of successful existing agribusiness, their knowledge in business plan preparation and their leadership experience. In contrast to previous studies (Cassol et al., 2022; Rusu et al., 2022; Zakaria et al., 2014), demographic variables such as age, gender, and education are not influencing factors of students’ EI. Although, researchers like Díaz-García & Jiménez-Moreno (2010) found a lack of gender difference in entrepreneurial intention. Existing role inspiring entrepreneur role model was not a predictor of EI, in continuation of previous study (Nowiński & Haddoud, 2019) where role model would predict entrepreneurial intentions only when combined with positive attitudes towards entrepreneurship. Similarly to Cassol et al. (2022) who found, in the case of Brazil, that entrepreneurship education was not a determinant of EI, we found that entrepreneurship education does not have direct influence on students’ EI. Instead, knowledge in business plan preparation was found as a direct determinant of agricultural engineering students’ EI. This result is in line with previous study on business creation among Haitian university graduates (Paul et al., 2021), it is also consistent with Boukamcha (2015). Rusu et al. (2022) recently found a negative relative relation between entrepreneurship education and EI. They also found a significant relation between access to finance and EI while our research showed no relation between available resources and EI. A possible explanation is that no start-up financing mechanism already exists in Haiti.

50In addition, family entrepreneurial background and entrepreneurship network were not significantly associated with students’ EI. In the context of Haiti, peasant farmers are not considered as entrepreneurs and formal agribusinesses exist in very few numbers. Most of the respondents declared not having family in business. As discussed below, their intention is determined more by their personal innovativeness than their network characteristics.

51Students’ search for autonomy was the most important factor influencing entrepreneurial intention. A student with strong search for autonomy was 4.24 times (AOR = 4.246; 95 % CI: 2.203 – 8.183) likely to have EI than a student with no such personality trait. In the same way, A student with experience in leadership was 2.69 times (AOR = 2.694; 95 % CI: 1.053 – 6.889) likely to have EI than a student with no such experience. In the existing literature, search for autonomy and leadership ability are considered as two ingredients for innovation (Burcharth et al., 2017). In the particular context of Haiti, these significant determinants of EI are very meaningful, since they indicate that in a hostile environment, only those who can pursue their goals with passion, motivation and inspiration around them can have success.

52Search for autonomy has been discussed previously as an important entrepreneurial personality trait (Al-Qadasi et al., 2023). Our result is consistent with previous researchers arguing that more often Haitians create individual businesses for cultural reasons (Lundahl, 2010; Paul & Francois, 2023). It also suggests that individual personal attitude is more influencing than family or social pressure on student's EI, since both family entrepreneurship background and entrepreneurial network were not associated with students’ EI. This result confirms previous finding by Bustamante et al. (2020).

53This research aimed, on the one hand, to understand the prevalence of entrepreneurial intention (EI) among students in agricultural engineering schools in Haiti, in a context of risky agricultural environment. The results revealed that they have a high intention to develop business. On the other hand, this study sought to understand the factors influencing students’ EI. The results showed that demographic factors, family and network entrepreneurial background are not associated with students’ EI. Contrariwise, according to our findings, the search for autonomy, students’ identification of a successful existing agribusiness, their knowledge in business plan preparation and their leadership experience are factors that determined their EI.

54The research findings suggest implications for policymakers wishing to encourage young skilled people to choose agricultural entrepreneurship instead of migration in the context of crisis and adverse business environment. Entrepreneurial opportunity exists along the food systems, in the particular context of food insecurity in Haiti (Paul, 2022). Policymakers should train skilled people in business plan preparation in their particular field of competence. The study suggests that to fostering entrepreneurship, they should focus on developing individuals' personal attitude (such as autonomy and leadership) rather than relying on the perceived family or social pressure to become an entrepreneur.

55Public policy interventions can also be focused on how to develop autonomy and leadership for agricultural engineering students in order to support entrepreneurship in the agricultural sector. It will be important to review the curricula of agricultural engineering schools in order to include training in business plan preparation. Administrators of agricultural engineering schools should seriously consider the opportunity to allow business plan preparation as final thesis for students interested to create their agribusiness. The government should create financial funds to support innovative agribusiness projects carried by students who show entrepreneurial intention instead of migration intention, particularly during those times of western selective immigration policies that encourage brain drain in developing countries (Di Martino, 2023).

56One of the limitations of this research is related to the data. As this was a cross-sectional study, it could not infer causality between different predictors and EI. It also focused only on agricultural engineering students. Future research can track cohorts of students to better observe their entrepreneurial intention, attitudes and activities as they try to effectively create their businesses.