1. Introduction
Entrepreneurship is regarded as one activity that influences the country’s development and strategic direction. The establishment of new businesses has a significant impact on a country’s economic growth (Ribeiro-Soriano, 2017). Similarly, governments in many countries have recognized new businesses’ positive and widespread influence on job creation, innovation, and practical value creation (Davidsson et al., 2006; Girma et al., 2008). Also during this time, according to a study published by the International Labor Organization (ILO, 2020), six of the nine economies with available data saw an increase in the youth unemployment rate: Japan, Indonesia, Australia, Malaysia, and Vietnam, together with Hong Kong, China, recorded the biggest gain of 3 percentage points. Youth rates rose faster than adult rates in all of these economies. In Vietnam, Prime Minister Nguyen Xuan Phuc has emphasized creating conditions to promote startups since the country’s first regular meetings following the establishment of the new government and has designated 2016 as the year of startups in Viet Nam. A record-breaking 110,100 new firms were founded in 2016, according to the General Statistics Office of Vietnam (2016). Furthermore, a series of programs and contests promote entrepreneurship spirit, creating a playground for students to experience, such as young people starting a business and students with startup ideas (the number of ideas and projects attended, with only 200 in 2018, increased to 600 in 2020).
During the past decades, entrepreneurship has been widely studied and continues to receive the attention of domestic and foreign researchers because of the importance of entrepreneurship in promoting economic growth and job creation (Mcmullan & Long, 1987; Dejardin, 2000; Stel et al., 2005). Furthermore, entrepreneurship aids in the promotion of sustainable development by addressing environmental issues, public health, and economic problems (Hall et al., 2010; Goel & Joshi, 2017). Entrepreneurship is a planned and intentional behavior (Krueger et al., 2000), so the most important thing is to figure out what motivates students to go into business for themselves and start new projects when most young people would rather work for someone else. Shapero and Sokol’s (1982) Entrepreneurial Event model, and psychological factors, opened the way for the development and popularization of studies on factors affecting entrepreneurial intention. Turker and Selcuk (2009) stated that previous studies mainly focused on personality, but personality cannot be isolated from context, so the research team theorized and empirically tested the results. The results show that the factors supporting structure and education affect students’ intention to start a business. Gelard and Saleh (2011) emphasized contextual factors’ impact on students, including informal network factors related to friends, family, surrounding people, and educational support factors. The entrepreneurial orientation factor in our study converges with the above two factors, in which the informal network is only counted within the school environment.
In recent years, many Vietnamese universities have begun to emphasize entrepreneurship education. However, it has not met practical application needs and is purely theoretical (Bình, 2016). In addition, entrepreneurship education is still not popular, especially in places where there are not enough conditions for students to be exposed to the environment or have early startup orientations. Therefore, after graduation, many students still do not have a full concept of self-employment and career (Vân, 2017).
From previous studies, in this study, we expand the model, combining the following factors: psychology, capacity, capital (internal factors), and entrepreneurial orientation related to education, teachers, friends, and the school’s surroundings (external factors), providing a view from more angles. Most previous research papers have been done in many countries worldwide and are also quite popular in Vietnam. However, the previous research papers in Vietnam only focused on students of one university or a specific area in the country, such as Khuong and An (2016), Bui et al. (2020), and Hiền and Trang (2021), there are very few papers on the entrepreneurial intentions of Vietnamese students in general. Therefore, this paper’s main and new contribution is to help identify, through analysis based on empirical data, the use of quantitative research methods and convenience sampling for investigation convenience.
Since intention is considered the best predictor of behavior, we utilize entrepreneurial intention as the dependent variable (Ajzen, 1991). The questionnaire was designed and developed based on a literature review. In this study, we test it on a representative sample of students at universities in Vietnam. Therefore, based on these results, several considerations have been made to address the above limitations in considering entrepreneurial intentions from various aspects, including (1) Self-expectation (Shiri et al., 2012; Dehghanpour Farashah, 2015), (2) Attitude (Lüthje & Franke, 2003; Nguyen, 2017; Phan Tan, 2021), (3) Self-competency (Sánchez, 2013; Nghia et al., 2021), (4) Perceived feasibility (Shapero & Sokol, 1982; Krueger & Brazeal, 1994), (5) Entrepreneurial orientation (Turker & Selcuk, 2009; Lingappa et al., 2020), (6) Finance (Teshome, 2014; Wongnaa & Seyram, 2014; Ngo et al., 2022). Finally, adding an empirical database to the research model related to the entrepreneurial intention by assessing whether or not and how to perform for factors such as self-expectation, personal competency, entrepreneurial orientation, and finance influence the intention to start a business. Research results will be a scientific basis for the Government to plan better policies in the future, set appropriate support orientations, encourage students to participate in entrepreneurship, and improve knowledge, skills, and attitudes needed as luggage when starting a business later.
2. Literature Review
2.1. Theoretical Background
Krueger (1993) defines entrepreneurial intentions as a commitment to starting a new business. Entrepreneurs with entrepreneurial intentions have precursor attitudes and awareness of social norms regarding entrepreneurship, forming the content of their intention (Bird & Jelinek, 1989). Their mental state can also influence their intention to become an entrepreneur, such as desire, wish, and hope (Peng et al., 2013). The Entrepreneurial Event model (SEE) by Shapero and Sokol (1982) and the Theory of Planned Behavior (TPB) by Ajzen (1991) are often used as research frameworks in previous studies on entrepreneurship. While SEE showed that perceived desirability, feasibility, and propensity to act impact entrepreneurial intention, TPB indicated the following factors: attitude, subjective norm, and perceived behavioral control. Krueger et al. (2000) compared these two models. They demonstrated their applicability for future studies, in which TPB has a slightly higher ability to assess intention, but both models are generally equally beneficial.
In conclusion, we divide factors influencing startup decisions into two main groups: internal and external factors. Internal factors comprise personality, self-expectation, attitude, self-competency, experience, and funding source. (Karabulut, 2016; Khuong & An, 2016), At the same time, external factors include macro factors such as economic situation, public policy, culture (Kristiansen & Indarti, 2004; Ashourizadeh et al., 2014; Wal, 2015; Ozaralli & Rivenburgh, 2016) and school environment, funding source, educational program, family background (Turker & Selcuk, 2009; Zhang et al., 2014; Lingappa et al., 2020).
2.1.1. Self-Expectation
Entrepreneurs are ingenious and creative in increasing their wealth, power, and prestige (Baumol, 1996). This would mean that individuals start their own businesses when or because their rewards from wealth, power, and status are prestige (Douglas & Shepherd, 2002). Therefore, we can see that expectation about the results impacts entrepreneurial intention (Dehghanpour Farashah, 2015), up to 72,5% in the study of Shiri et al. (2012). As a result, we predict that self-expectation would positively influence entrepreneurial intention.
2.1.2. Entrepreneurial Attitude
According to the Theory of Planned Behavior of Ajzen (1991), attitude toward behavior refers to the degree to which a person assesses the results obtained from performing the behavior, a favorable or unfavorable evaluation. The intention to start a business is stronger in those with a positive attitude towards work, independence, risk, and income (Douglas & Shepherd, 2002). Having the same viewpoint, Lüthje & Franke (2003) suggested that the entrepreneurial attitude is the most significant precursor to an entrepreneurial intention. Nguyen (2017) and Utami (2017) all developed points based on the Theory of Planned Behavior to show that attitude positively influences entrepreneurial intention.
2.1.3. Personal Competency
Sánchez (2013), based on the human capital theory, indicated that individuals with greater competencies would have higher entrepreneurial intention. Sharing the same viewpoint, in research conducted with a sample size of 1200 Vietnamese students, Nghĩa et al. (2021) highlighted a positive interaction between personal competency and entrepreneurial intention (up to 36.2%). Impulsivity, emotional self-awareness, and problem-solving abilities affect directly, while creativity indirectly affects entrepreneurial intention (Yıldırım et al., 2019). However, Yousaf et al. (2015) noted that students might succeed as entrepreneurs without the necessary entrepreneurial skills and competencies as long as they have an entrepreneurial spirit, are desirable to others, and have community support.
2.1.4. Perceived Feasibility
Perceived feasibility is one of the three important factors affecting entrepreneurial intention in the Entrepreneurial Event model (SEE) of Shapero and Sokol (1982) and the Potential Entrepreneurial model of Krueger and Brazeal (1994), in which perceived feasibility has the greatest impact (Krueger Jr & Brazeal, 1994). Perceived feasibility in SEE also corresponds to perceived behavioral control in the Theory of Planned Behavior (TPB) of Ajzen (1991) and Krueger and Brazeal (1994). Fitzsimmons and Douglas (2011), Hung and Pha (2016), and Minh (2019) pointed out that perceived feasibility is positive and strong in connection with entrepreneurial intention. Nevertheless, Zhang et al. (2014), in research with 494 students from 10 universities, indicated that perceived feasibility does not affect student intention to start a business. In addition, the research results of Guerrero et al. (2008) illustrate that most university students believe starting a new company is desirable, despite having a negative opinion of its feasibility.
2.1.5. Entrepreneurial Orientation
When analyzing the relationship between entrepreneurial orientation and entrepreneurial intention, numerous previous studies were mainly based on Miller’s (1983) original conceptualization of innovativeness, proactiveness, and risk-taking. Autonomy and competitive aggressiveness, which Lumpkin and Dess (1996) identified as two additional elements, are essential to the entrepreneurial orientation idea. However, the entrepreneurial orientation factor in this study refers to external factors such as education and Training, teachers’ encouragement, and orientation from teachers or friends. A young person may likely choose an entrepreneurial profession if a university offers sufficient information and motivation about entrepreneurship (Turker & Selcuk, 2009). Peers also have a positive impact on entrepreneurial intention (Kacperczyk, 2013; Lingappa et al., 2020) by developing entrepreneurial attitudes and career goals (Giannetti & Simonov, 2009) or having a common language and the same intention (Lingappa et al., 2020). Nevertheless, Barral et al. (2018) emphasized that the development of entrepreneurial ambition is not encouraged by the academic environment, according to Barral et al. (2018).
2.1.6. Finance
It is argued that raising capital is the principal problem of potential entrepreneurs, and individual entrepreneurs feel they need the most help with finance (Blanchflower & Oswald, 1998). Previous studies suggest that financial access may hinder a person’s entrepreneurial intention. This point is emphasized in a study on students’ views of Teshome (2014), young people have fewer assets and savings available. Hence, the biggest sources of capital for startups come from close family members and friends (Bygrave et al., 2003). In the case of students at Leeds Metropolitan University, more than 50% consider financial risk a barrier because they need financial stability after graduation and fear default or loans (Robertson et al., 2003). Individuals who can access capital are more likely to decide to start a new business (Wongnaa & Seyram, 2014). However, in VietNam, financial accessibility does not affect entrepreneurial intention unless accompanied by entrepreneurial behavioral control, according to Nguyen (2020). It is also suggested that capital is the least important factor affecting students’ intention to start a business (Định et al., 2021).
2.2. Hypotheses
Based on the above discussion, it is hypothesized that:
H1: Self-expectation has a positive correlation with entrepreneurial intention.
H2: Attitude has a positive correlation with entrepreneurial intention.
H3: Personal competency has a positive correlation with entrepreneurial intention.
H4: Perceived feasibility has a positive correlation with entrepreneurial intention.
H5: Entrepreneurial orientation has a positive correlation with entrepreneurial intention.
H6: Finance has a positive correlation with entrepreneurial intention.
3. Methodology
3.1. Research Methods
The research uses quantitative methods, and convenience sampling is the main method. To measure the factors influencing the entrepreneurial intentions of all university students nationwide. The reason for choosing this audience is because this target group is well-positioned to start a business. Students have the advantage of being young, not afraid of difficulties, and not under pressure from family and financial burdens. Besides, the university is also a place to help students cultivate specialized knowledge and generate many business ideas, promoting creativity. Method of exploratory factor analysis EFA is used to test the value of the scale, collapse the variables in the data set, and set of closely related variables that combine to form representative factors; Correlation analysis and linear regression to determine the degree of influence of factors on the intention to start a business. At the same time, compare the difference between male and female students on the factors influencing startup intention. The study uses a non-probability sampling method with a convenient sampling technique because of its convenience, ease of access, and information retrieval. According to Hair (2009), the sample size to use EFA should be at least 50 and preferably 100, with a 5/1 observation/measurement ratio, which means that one measure requires at least five observations. With 26 observed variables of the scales in this research to conduct EFA, the minimum sample size of the study is 130. Fidell and Tabachnick (2003) state that the minimum sample size is n ≧ 50 + 8 * p, where p is the number of independent variables. As a result, the minimum sample size is n ≧ 8 * 6 + 50 ⇔ n ≧ 98. After observing the requirements of EFA analysis and multiple regression analysis and considering the time limit, the number of observations of the study is 656 will be appropriate. The data source was collected through a direct survey of students using a questionnaire designed based on a literature review consisting of two parts:
Part 1: Questions in the form of multiple-choice or yes-no questions, used to collect respondents’ personal information such as name, age, gender, etc.
Part 2: Questions to collect information about business intention and its influencing factors. Reliability of the measurement uses 5 points Likert scale (1-Strongly disagree, 2-Disagree, 3-Neutral, 4-Agree, 5-Strongly agree) to collect data, measuring the degree of agreement of respondents for each statement. After collecting data from survey subjects, it is coded, cleaned, and analyzed through descriptive statistics, reliability testing of Cronbach’s Alpha scale, and multivariable linear regression with the support of SPSS22 software.
The graph (Figure 1) depicts the differences in elements in school that influence male and female students’ intentions to start a business. Men have a clearer and more consistent career orientation than women. Another factor is that relationships such as family and friends positively influence men’s entrepreneurial intentions. Also according to the chart, it can be seen that the motivation and encouragement of teachers in both sexes are equal and female is somewhat higher than that of males. Finally, men have a greater accumulation of life experiences and learning in the learning process when equipping themselves with the required expertise and knowledge.
Figure 1: Gender Analysis
The results show that the two sexes are not too different and similar, especially regarding fairness in encouraging students from teachers. However, regarding career orientation, the above findings align with the current situation in Vietnam, where it is believed that men are better suited to hold positions of power than women. The above results are consistent with the studies of Georgellis and Wall (2005), and Kirk and Belovics (2006) argued that this disparity is because women prioritize balancing work and family needs, only seeing entrepreneurship as an alternative to part-time work. Meanwhile, men are more willing to take on challenging work and see entrepreneurship as a means of achieving wealth.
3.2. Research Models
After reviewing domestic and foreign documents, we selectively inherited the factors affecting students’ entrepreneurial intention in related studies (Tu & Tien, 2015; Định et al., 2021). It is also based on two available research frameworks: the Entrepreneurial Event model of Shapero and Sokol (1982) and the theoretical model of planned behavior (TPB) of Ajzen (1991). TPB showed that entrepreneurial intention is affected by three main factors: personal attitude, subjective norm, and perceived behavioral control. In contrast, SEE showed that perceived desirability, perceived feasibility, and propensity to act impact entrepreneurial intention. Therefore, we find that the addition and renewal of factors, including self-expectation, personal competency, entrepreneurial orientation, and finance, are necessary to increase the predictive ability of the models. This study proposes a theoretical research model including six factors affecting entrepreneurial intention (Figure 2).
Figure 2: Research Model
4. Results
Table 1 reports the results of the reliability test using Cronbach’s alpha.
Table 1: Reliability Test Using Cronbach’s Alpha
Test results for EXP variables demonstrate that Cronbach’s Alpha if Item Deleted of EXP4 variable exceeds Cronbach’s Alpha coefficient = 0.854. Still, the overall correlation coefficient for the variables EXP1, EXP2, EXP3, etc., is suitable (≥0.3). The EXP1, EXP2, EXP3, and EXP4 are excellent measuring scales representing the variable EXP since they fulfill the reliability requirements and have Cronbach’s Alpha coefficient = 0.854 ≥ 0.8. Therefore, we do not need to remove the EXP4 variable from the EXP variable.
For COM variables, the test findings for COM variables indicate that Cronbach’s Alpha reliability coefficient of the COM variable will increase rise if the Item deleted from COM5 variables is greater than Cronbach’s Alpha coefficient = 0.696, and the Corrected Item of COM5 is less than 0.3. To improve the scale’s dependability, we must take the COM5 variable out of the COM variable. All remaining COM variables have adequate correlation coefficients (≥0.3), according to the reliability test still conducted on variables COM1, COM2, COM3, and COM4. Cronbach’s Alpha coefficient = 0.696 ≥ 0.6, so the variables COM1, COM2, COM3, and COM4 are adequate measurement scales for COM.
The test results for ATT variables show that Cronbach’s Alpha coefficient is greater than Cronbach’s Alpha coefficient = 0.886 if the Item is deleted from the ATT variable. The ATT variables have a reasonable total correlation coefficient (≥0.3). Cronbach’s Alpha coefficient = 0.886 ≥ 0.8, so the variables ATT1, ATT2, ATT3, and ATT4 meet the dependability requirements and are an excellent measuring scale for representing the variable ATT. As a result, there is no need to remove the ATT4 variable from the ATT variable. The test results for FEA variables show that Cronbach’s Alpha coefficient if the Item deleted of FEA2 and FEA5 variables is greater than Cronbach’s Alpha coefficient = 0.691 and the Corrected Item of FEA5 variable is less than 0.3, indicating that the FEA5 variable should be removed from the FEA variable to improve the scale’s dependability. Continuing to run the variable reliability test FEA1, FEA2, FEA3, and FEA4 on Cronbach’s Alpha scale reveals that all remaining FEA variables have adequate correlation coefficients (≥0.3). Because Cronbach’s Alpha coefficient = 0.691 ≥ 0.6, the FEA1, FEA2, FEA3, and FEA4 measuring scales adequately represent the FEA variable. As a result, the FEA2 variable does not need to be removed from the FEA variable.
The test results for ORI variables show that y is greater than Cronbach’s Alpha coefficient = 0.865 if the Item is deleted from the ORI3 variable. Nonetheless, the ORI1, ORI2, ORI3, and ORI4 have a suitable total correlation coefficient (≥0.3). Cronbach’s Alpha coefficient = 0.865 ≥ 0.8, indicating that the variables ORI1, ORI2, ORI3, and ORI4 meet the dependability requirements and are an excellent measuring scale for representing the ORI. As a result, the ORI3 variable does not need to be removed from the ORI variable.
The test results show that the observed variables FIN have an appropriate total variable correlation coefficient (≥0.3) for FIN variables. Cronbach’s Alpha coefficient = 0.865 ≥ 0.8, indicating that variables FIN1, FIN2, and FIN3 meet the requirements for reliability and are an excellent measurement scale for the variable FIN.
4.2. Regression Results
We obtain the adjusted R2 value = 0.026338 from the multiple linear regression model (Table 2), indicating that the independent variables in the model can explain 2.63% of the change in the dependent variable when Prob > 0.1, the independent variable has no statistical significance, according to a 90% confidence level. Put another way. The independent variable does not affect the dependent variable. Prob(GEN) = 0.3377 > 0.1; that is, with 90% confidence, we can say that GENDER does not affect the Startup decision of young people. In other words, there is no difference between the sexes in starting a business. Prob (AGE) = 0.0778 < 0.1. That is, with 90% confidence, we can say that AGE has a strong impact on the Startup decision of young people. In other words, young people tend to make entrepreneurial decisions as age increases. Prob (QUA) = 0.5102 > 0.1; that is, with 90% confidence, we can say that Qualification does not affect the Startup decision of young people. In other words, QUA does not affect the decision to start a business. Prob (JOB) = 0.0983 < 0.1. With 90% confidence, it can be concluded that JOB strongly impacts young people’s startup decisions. In other words, the more precarious young people’s jobs are, the more likely they are to start a business. Prob (EXPEC) = 0.7214 > 0.1; that is, with 90% confidence, it can be said that EXPEC does not affect the Startup decision of young people. In other words, self-expectation is not the key for young people to make entrepreneurial decisions.
Table 2: Regression Results
Prob (COM) = 0.0809 < 0.1. That is, with 90% confidence, it can be said that COMPETENCE has a major impact on young people’s startup decisions. Since Coefficient (COM) = –0.24, with 90% confidence, it can be said that COM harms START. Prob (ATT) = 0.2833 > 0.1, that is, with 90% confidence, it can be concluded that ATTITUDE does not affect the Startup decisions of young people. In other words, although young people have a positive attitude towards work, independence, risk-taking, and income, they are unlikely to start a business. Prob (FEA) = 0.8405 > 0.1, that is, with 90% confidence, it can be said that feasibility does not affect the Startup decisions of young people. In other words, perceived feasibility is not positive and does not create influence young people in making entrepreneurial decisions. Prob (ORI) = 0.0844 < 0.1. With 90% confidence, it can be concluded that ORIENTATION significantly influences young people’s startup decisions. In other words, education in schools plays the most important role in students’ decision to start a business later. Since Coefficient (ORI) = 0.171453 is a positive value, ORI positively affects START. Prob (FIN) = 0.7598 > 0.1, that is, with 90% confidence, it can be said that finance does not affect the Startup decision of young people.
This table’s Durbin-Watson values can be used to evaluate the phenomenon of first-order series autocorrelation. The results do not violate the first-order series autocorrelation assumption because the value DW = 2.337456 falls between 1.5 and 2.5. T-test is used to analyze the influence of independent variables on students’ entrepreneurial intention. Looking at the values in the table shows that today’s young people are increasingly inclined to start a business, emphasizing the importance of school education to students’ decision to start a business. They cannot start a business without the support and encouragement of teachers and friends and the proper guidance, knowledge, and skills.
5. Conclusion
Six determinants were investigated: (1) self-expectation, (2) attitude, (3) self-competency, (4) perceived feasibility, (5) entrepreneurial orientation, and (6) finance. This result is quite surprising that self-expectation, attitude, perceived feasibility, and finance are confirmed not to be the factors affecting entrepreneurial intention. The results demonstrate that only two factors impact Vietnamese students’ intention to become entrepreneurs: self-competency and entrepreneurial orientation. There is a big detrimental influence from self-expectations and a significant positive impact from entrepreneurial orientation.
Self-competency factor: According to the research findings, self-competency is detrimental to entrepreneurial intent. At the same time, Sánchez (2013) supposed that individuals with greater competencies would have higher entrepreneurial intentions. Practical skills and entrepreneurial competencies would be an advantage for students choosing careers. Therefore, they tend to join a large company to work for someone else instead of starting their own business. According to Camelo-Ordaz et al. (2016) and García and Cañizares (2010), students with extensive skills and knowledge often tend to be more careful when making decisions. Starting a business will present many challenges and difficulties that require students to make a difference, fearing failure.
The entrepreneurial orientation factor is the most critical element influencing a student’s intention to start a business. Can students start a business without the right orientation, the knowledge and skills taught by the teachers, the encouragement from the school, and the supportive friendships? These are the most basic conditions for young people to enter the market and start a business. The above research results are consistent with Turker and Selcuk’s (2009) and Lingappa et al. (2020) studies. Therefore, schools play an essential role in promoting students’ entrepreneurial intention; entrepreneurship becomes a part of education.
Based on the findings of the study, the authors make the following recommendations for schools to promote entrepreneurship and increase students’ entrepreneurial awareness and competency:
Essential Knowledge and Skills: focusing on how students can apply theories into practice and improve the skills needed to start a business, such as leadership skills, strategic planning skills, financial management, communication skills.
Encouragement from teachers: Teaching should be combined with spreading inspiration and encouragement. In addition, they emphasize entrepreneurship’s values to society and individuals. Because the teacher is the one who directly transmits knowledge to students, they should have effective teaching strategies.
Relationship development: Creating a favorable environment for students to nurture and materialize startup ideas through competitions, clubs, and startup orientation programs. On that basis, helping students get acquainted, connect, and promote the spirit and culture of entrepreneurship. In addition, they act as a bridge between the students and investors by organizing talk shows by experienced business people.
Career orientation: The startup ecosystem is gradually influenced by unclearly-oriented students, and hence when facing difficulties, they are easily discouraged and then give up, while starting a business is a challenging journey. Therefore, the school should have career counseling activities associated with the market’s needs and each individual’s strengths and passions, incentivizing students to choose an appropriate career.
However, there might be some limitations contained in this research. We believe that the small size of the sample does not permit generalization. The research period is too short to allow relationship testing among variables and make a more objective assessment of the intention to start a business. In addition, many other factors may become potential determinants of entrepreneurial intention that have not been considered in this study, such as government support, personality, and family background. Further studies can overcome these limitations by increasing the sample size and research period to make the sample more representative. Future studies can also examine other specific factors that may affect entrepreneurial intention, such as government support, personality, and family background—in addition to finding the exact effect on each other in more depth and understanding how all the factors are significantly related.
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