Interplay of Influencing Factors Shaping Entrepreneurial Intention: Evidence from Bangladesh

Abstract

This study examines the relationships between risk-taking propensity (RTP), entrepreneurship education support (EES), need for achievement (NFA), and entrepreneurial intentions (EI) of Bangladeshi university students, as well as the mediating roles of attitude toward entrepreneurship (ATE), subjective norms (SN), and perceived behavioral control (PBC). Using partial least squares structural equation modeling (PLS-SEM), the study was conducted with a sample of 381 respondents. Results show that attitudes play a mediating role in the relationship between RTP and EI, and RTP has a direct positive effect on attitudes toward entrepreneurship and EI. Although EES does not have a direct effect on EI, it does have a positive effect on all other components of the theory of planned behavior (TPB), which in turn influences EI. Perceived behavioral control and attitudes toward entrepreneurship serve as full mediators of the EES-EI connection. Subjective norms, on the other hand, have no relationship with EI and do not serve as a mediator between the EES and EI relationship. However, NFA and EI do not have a direct relationship; NFA influences EI indirectly via perceived behavioral control, which in turn influences EI directly. This research contributes to the existing literature by offering significant theoretical and practical insights into the factors that influence entrepreneurial intentions among university students in developing economies.

1. Introduction

Entrepreneurship is widely seen as a key driving force in any country’s economic growth, employment opportunities, and innovation. Moreover, entrepreneurship is generally considered the main driver of social innovation and economic growth of a country (Holloway and Pimlott-Wilson 2021; Talukder and Lakner 2023). That is true for Bangladesh as well. Bangladesh, a south Asian country, has a total population of 165.16 million, with 20% of that made up of young adults (age 15–24) (Bangladesh Bureau of Statistics 2022). It is worth noting that the overall unemployment rate in the country is experiencing a gradual increase. Specifically, the young unemployment rate in Bangladesh stands at 12.93% (Statista n.d.a, n.d.b). This problem highlights the fact that the people of Bangladesh, especially the younger generation, cannot depend exclusively on the government and corporations for employment but rather must start their own businesses to survive (Shahriar et al. 2021). Since entrepreneurship is regarded as a key driver of economic growth, innovation, and job creation, it is one of the most popular alternative solutions for tackling unemployment issues. However, unemployment among Bangladeshi university graduates is a serious problem on a national scale (Rahaman et al. 2020). So, there is a growing need for entrepreneurship in Bangladesh to address the issue of youth unemployment (AI Saiqal et al. 2019). The government of Bangladesh is aiming to foster an entrepreneurial environment by offering financial support to the younger generation so that the country’s economy can grow overall (Startup Bangladesh Limited n.d.). However, university graduates in Bangladesh believe it is better to work for the government or other organizations instead of starting their own businesses (Karmoker et al. 2020). There has been a parallel rise in both the rate of unemployment and the number of university graduates in recent years (Uddin et al. 2022). Unfortunately, the current job market is not ready to employ all the country’s university grads, which is leading to economic inequality (Rahman et al. 2022). Hence, entrepreneurship and self-employment, in this context, can provide graduates with promising career paths that help to propel the socioeconomic development of the nation. A great deal of research has focused on the underlying factors of entrepreneurship intention and how it affects the development of an economy, especially in the case of youngsters (Ogunsade et al. 2021).

The process of entrepreneurial activity begins with an individual’s entrepreneurial intention. For someone who wants to start a new venture, their entrepreneurial intentions are very important because it show the way they think, which guides their actions and decisions (Bird 1988; Krueger et al. 2000; Shapero and Sokol 1982). Moreover, an entrepreneurial intention is a way of thinking that guides one’s focus, knowledge, and actions in the direction of a specific objective. It is the primary determinant of an individual’s actions that can motivate individuals to become entrepreneurs (Ozaralli and Rivenburgh 2016). Still, practically every nation faces the problem of how to foster an entrepreneurial spirit and alter individual perceptions toward entrepreneurship (Shah et al. 2020). Universities are key players in creating and growing an economy based on entrepreneurship (Talukder et al. 2024). Furthermore, it is widely acknowledged that entrepreneurship education provided by the university plays a significant role in assisting students in comprehending and cultivating entrepreneurial intention (Lv et al. 2021). Entrepreneurs with higher levels of education also have a better chance of making a positive impact on the local economy compared to those with lower levels of education (Taatila 2010). On the other hand, important personality traits that influence students’ intentions to start their own enterprise include the need for achievement and a risk-taking propensity (Brockhaus 1980; Murray and McAdams 2007). Moreover, risk-taking propensity can change attitudes toward entrepreneurship (Chanda and Unel 2021). A higher degree of entrepreneurial intention is associated with a higher risk tolerance (Hmieleski and Corbett 2006). Individuals with a strong need for achievement are more likely to engage in creative and innovative activities, such as entrepreneurship, that entail an individual’s responsibility for task outcomes than those with a low need for achievement (McClelland 1961). The factors that shape students’ intentions to start their own businesses should be understood. This is because decision-makers can learn what inspires youngsters to pursue entrepreneurial careers. Likewise, the improvement in the economy has encouraged researchers to focus on this aspect of entrepreneurship (Rahman et al. 2017).

Entrepreneurial activities take time to flourish (Zamrudi and Yulianti 2020). Furthermore, it involves the interaction of cognitive processes and behavioral attitudes with socioeconomic and cultural influences. Previous research has confirmed that persons with a strong and positive entrepreneurial intention (EI) have a high potential for entrepreneurship (Ozaralli and Rivenburgh 2016; Sampene et al. 2022). The relationship between the theory of planned behavior and entrepreneurial intention proposed by Ajzen (1991) assumes personal attitudes, subjective norms, and perceived behavioral control as antecedents of entrepreneurial intention. In this study, researchers consider risk-taking propensity, entrepreneurship education support, and the need for achievement as antecedents of the theory of planned behavior model, as they influence attitudes, subjective norms, and perceived behavioral control. A high risk-taking propensity promotes positive attitudes toward entrepreneurship and increases confidence in handling uncertainties (Hmieleski and Corbett 2006). On the other hand, entrepreneurship education has a positive impact on attitudes, fosters a supportive social environment, and increases confidence by providing skills and knowledge (Ozaralli and Rivenburgh 2016). More importantly, a strong need for achievement drives individuals to reach difficult goals, promotes positive attitudes, and boosts self-efficacy (Tessema Gerba 2012). These elements influence the TPB framework’s predictions about entrepreneurial intention.

In the current study, the researchers investigated how a potential entrepreneur’s cognitive condition is influenced by risk-taking propensity (RTP), entrepreneurship education support (EES), and need for achievement (NFA) in relation to the intention to start a new business venture. Moreover, the researchers also investigated the mediating effect of attitudes, subjective norms, and perceived behavioral control in the link between risk-taking propensity (RTP), entrepreneurship education support (EES), need for achievement (NFA), and entrepreneurship intention (EI). This study has three exploratory objectives: (1) to examine the relationship between the TPB and entrepreneurial intention from the perspective of university students in Bangladesh; (2) to demonstrate a modified model of the TPB, whether risk-taking propensities, entrepreneurial education support, and need for achievement are related to entrepreneurial intention; and (3) to provide evidence that the TPB is a useful construct for understanding the relationship of university students’ entrepreneurial intention (EI). With these broad goals in mind, researchers were able to examine the entrepreneurial mindset of university students of Bangladesh from personality traits (risk-taking propensity, need for achievement), entrepreneurship education support, and TPB perspective. This research aims to investigate these major questions.

RQ1. Is student EI influenced by RTP, EES, NFA, ATE, SN, and PBC?

RQ2. What roles do ATE, SN, and PBC play as mediators between students’ intentions to start their own business and the factors that influence RTP, EES, and NFA?

The study used the Partial Least Square Structural Equation Model (PLS-SEM) to test the proposed hypothesis. There are three major contributions to this research. First, this research expands upon the existing literature on EI, TPB, EES, and personality traits. Previous research has not specifically addressed personality traits, EES, TPB, and EI but has instead examined entrepreneurial intention in various settings (Liñán and Chen 2009; Munir et al. 2019; Ng et al. 2021). However, this research shows that all TPB dimensions (except SN) have positive impacts on the EI of Bangladeshi university students. Second, we investigated the impact of three antecedents (risk-taking propensity, entrepreneurship education support, and need for achievement) on TPB dimensions and EI in Bangladeshi students, in contrast to previous studies that tended to focus on TPB and entrepreneurial intention (Hossain et al. 2023, 2019; Karmoker et al. 2020; Rahaman et al. 2020a; Rahman et al. 2022; Ramadani et al. 2022; Uddin et al. 2022; Uddin and Bose 2012). Through this lens, we can emphasize how risk-taking propensity, entrepreneurship education support, and need for achievement can all contribute to explaining and shaping TPB dimensions, which in turn encourages entrepreneurship intention in Bangladeshi university students. Third, this research suggests a revised conceptual model for EI that incorporates the TPB dimensions and three additional variables as predictors. The findings can provide valuable insights to policymakers and universities that are committed to an entrepreneurial culture with useful strategies and directions. Researchers might start by looking into this question to find out what motivates and inspires young individuals to become entrepreneurs.

The layout of the article goes as follows: the literature review, hypotheses, and conceptual model are all shown in Section 1. The sample, the method, and the data collection are all explained in Section 2. The results can be found in Section 3. Section 4 focuses on the discussion, while Section 5 presents limitations, future research avenues, and theoretical and managerial implications of the current study.

2. Literature Review, Hypothesis Development, and Conceptual Framework

2.1. Theory of Planned Behavior (TPB)

This research is grounded in Ajzen’s theory of planned behavior (Icek Ajzen 1991). Among socio-psychological theories, TPB is the most popular and widely used for comprehending and predicting the behaviors of individuals in many settings. Furthermore, many researchers in the social and behavioral sciences use this theory to better understand individuals’ behavioral intention, particularly when it comes to starting their own enterprise (Acheampong and Tweneboah-Koduah 2018; Henley et al. 2017; Sun et al. 2017). The Theory of Reasoned Action (TRA) has been improved upon by TPB, which allows for more precise intention prediction in relation to specific time and location. Attitude toward behavior, subjective norms, and perceived behavioral control are the three independent antecedents that make the TPB model. An individual’s attitude toward behavior is affected by how desirable they think it is to perform that behavior, which is helped by their beliefs about likely outcomes and how they feel about those outcomes (Armitage and Conner 2001). Subjective norms are the pressures people feel from their peers to behave in a certain way. These pressures are caused by normative views, which are what other people probably think about a behavior. Finally, perceived behavioral control is how easy or hard someone thinks it is to do a certain behavior based on their control beliefs. Control beliefs are how much someone thinks that the presence of factors that make a behavior possible or impossible affects that behavior.

In the context of entrepreneurship, attitude refers to an individual’s positive or negative evaluations of the process of establishing a new venture, subjective norms refer to an individual’s perception of the social pressure and expectations placed on them by family and pairs to start/not start a new business, and perceived behavioral control refers to the degree of control that an individual believes they have over the process of establishing a new business (Fretschner and Weber 2013). Furthermore, Ajzen (2002) made improvements to the theory of planned behavior model by including additional variables (attitudes, personality, and behavior). These variables include demographic, personal, social, and environmental elements, all of which might influence entrepreneurial activity. Both Shapero and Bird stressed the importance of individual traits and environmental circumstances in predicting entrepreneurial actions (Bird 1988; Shapero and Sokol 1982). Consistent with this assertion, the researchers sought to understand the role of entrepreneurship education and personality elements in influencing the intention to start a business. Furthermore, to predict TPB’s relationship with entrepreneurship intention, researchers looked at entrepreneurial education support and personality traits, including risk-taking propensity and need for achievement as predictors of TPB. This study adds to the literature on entrepreneurship education support, risk-taking propensity, need for achievement, and TPB in an emerging country setting by connecting the theory to the constructs under investigation.

2.2. Entrepreneurship and Entrepreneurship Intention

Entrepreneurship is considered the active process of discovering opportunities, coming up with new and innovative ideas, and collecting resources to start and run businesses that generate financial resources (Talukder et al. 2024). Moreover, entrepreneurship is a form of competitive behavior that generates new opportunities for employment, market expansion, and technological advancement. Entrepreneurship is often viewed as a pragmatic solution to the issue of youth unemployment. Entrepreneurs deal with uncertainty by using their imagination, leadership, and resourcefulness to turn business ideas into real ones. By coming up with new ideas and solving problems, they help the economy grow, create jobs, and move society forward. Since entrepreneurship greatly contributes to national economic growth via the creation of new jobs, innovation, creativity, and social development, it ought to be an integrated approach (Farrukh et al. 2019).

Intentions are consequences of some obvious antecedents that include attitudes, personality, and core self-efficacy of individuals. Moreover, intention is considered a planned behavior. An individual’s entrepreneurial aspirations can be defined as their desire to establish a new enterprise (Krueger 2017). Additionally, the identification of a unique and appealing business opportunity may serve as a catalyst for the development of entrepreneurial aspirations (Douglas 2009). An individual’s propensity to launch and run their own business is strategically determined by his entrepreneurship intention. Various studies have attempted to define EI from different perspectives; hence, there is no formal definition of entrepreneurial intention. When a person sincerely believes in starting a new venture and makes a deliberate strategy to execute it in the future, they are said to have entrepreneurial intentions (Thompson 2009). Therefore, an individual’s entrepreneurial intentions are crucial to their decision to launch a new business since they represent the mindset that underpins action and directs entrepreneurial decision making (Bird 1988; Krueger et al. 2000; Shapero and Sokol 1982). Intentions are the most fundamental factor in determining individuals’ behavior. In turn, strong intentions predict actual behavior enactment; however, extrinsic influences may impact the translation of intention into action. Behavior predictions or actual actions are more likely to succeed when there is a strong intention for them. A person’s actual actions are preceded by their intentions. Therefore, a career choice in entrepreneurship can be regarded as a deliberate action that can be elucidated through the lens of intention models.

2.3. Risk-Taking Propensity, Entrepreneurship Education Support, and Need for Achievement

An individual’s risk-taking propensity (RTP) can be considered as their tendency or readiness to participate in activities with unknown outcomes, resulting in either benefits or losses. It entails being willing to take risks, make choices, and seize opportunities regardless of the potential outcomes. A common argument is that entrepreneurs must be willing to accept risks, as launching a new business requires them to act and make decisions under conditions of uncertainty. A higher degree of entrepreneurial intention is associated with a higher risk tolerance (Hmieleski and Corbett 2006). Research conducted in Turkey by Gürol and Atsan (2006) reveled that student who exhibited an entrepreneurial spirit scored higher on the risk-taking propensity scale than their non-entering counterparts. The risk propensity is the best indicator of being an entrepreneur, among other traits, but it does not always have anything to do with how well an entrepreneur does (Zhao et al. 2009).

Entrepreneurial education support is crucial for creating an entrepreneurial ecosystem that encourages people to be entrepreneurs and helps them reach their goals. The goal of entrepreneurship education programs is to assist individuals in developing the mindset, set of skills, and capacity for risk taking that will propel them to achieve their entrepreneurial goals. Moreover, talents like innovation, perseverance, and strategic thinking can be honed through an entrepreneurship education program (Krueger 2009). Furthermore, entrepreneurship education emphasizes how critical it is for students to further develop their creative competency (Jones et al. 2021). Entrepreneurship education provided by universities is crucial for fostering a favorable inclination toward entrepreneurship. Ensuring the effective design and implementation of the educational process for EE is crucial (Jones 2019; Jones et al. 2014a). When it comes to EE, for instance, experimental teaching approaches (learning by doing) have been shown to boost individuals’ aspirations to start their own businesses (Nabi et al. 2017). In addition, individuals can shape their entrepreneurial intention through the practical learning and engagement opportunities provided by entrepreneurship education (Kaffka and Krueger 2018). Education in entrepreneurship plays a significant role in the cultivation of human capital by educating individuals with the information, abilities, mindset, and networks needed to pursue entrepreneurial endeavors (Hindle et al. 2009). Through the cultivation of entrepreneurial mindsets, entrepreneurship education equips individuals to fearlessly seize business opportunities, foster innovation, and play a role in driving economic progress (Douglas 2009). Entrepreneurship education should focus on providing students the tools they need to learn skills for entrepreneurship that help to make them creative and willing to take risks (Nielsen and Gartner 2017). Entrepreneurship education (EE) is always changing and trying to find out what the best ways are to teach people how to be entrepreneurs (Maritz 2017). The goal of entrepreneurship education is to nurture and improve the enterprising drive, understanding, knowledge, and skills that are essential for starting and running a successful business (Ozaralli and Rivenburgh 2016).

The term need for achievement describes an individual’s motivation to work hard, accomplish their goals, and feel good about themselves afterward (Tessema Gerba 2012). Individuals with a strong need for achievement are more likely to engage in active, innovative, and creative activities, such as entrepreneurship, that entail an individual’s responsibility for task outcomes than those with a low need for achievement (McClelland 1961).

2.4. The Relationship between Risk-Taking Propensity, Attitudes toward Entrepreneurship, and Entrepreneurship Intention

A person’s risk-taking propensity can be defined as their level of tolerance to take risks that could potentially result in losses (Verheul et al. 2015). This tendency plays a significant role in determining whether someone chooses to work for themselves as an entrepreneur or serve a company. Risk-taking propensity can change attitudes toward entrepreneurship (Chanda and Unel 2021). A study with undergraduate students in Nigeria found that students’ willingness to take risks and past business experience are important factors in determining their desire to become entrepreneurs (Ilevbare et al. 2022). This finding is supported by the other studies conducted in Zimbabwe, the U.K., Turkey, and Portugal (Gurel et al. 2010; Ndofirepi 2020; Ramos et al. 2020). According to Ajzen, individuals form attitudes based on what they believe about the consequences of a behavior (Icek Ajzen 1991). Risk-taking propensity also has a positive relationship with attitudes toward entrepreneurship. The individual who has a high risk-taking propensity has more positive attitudes toward entrepreneurship (Ahmed et al. 2021). Agu (2021) emphasizes the role of attitudes toward innovation in affecting intentions to start a business, while Rueda Barrios et al. (2022) emphasize the predictive potential of attitudes in shaping entrepreneurial behavior. Entrepreneurial attitudes, including opportunity awareness, self-esteem, and risk readiness, play a crucial role in both the explanation of career selections and the increase in entrepreneurial intention (Ahmed et al. 2021). The model incorporates mediation impact, the key strength of EI, which is linked to ATE, and the propensity to take risks. The most recent findings suggest that ATE mediates the relationship between various individual/psychological factors and organizational outcomes, such as the one between EI and personality traits like risk-taking propensity (Farrukh et al. 2018; Munir et al. 2019). A previous study suggests that ATE consistently boosts EI (Anjum et al. 2021). Students who are self-assured, creative, and possess the abilities and mindset essential to start their own firm are more inclined to pursue entrepreneurship as a career path. ATE predicts EI position, but RTP is a distant antecedent. For that reason, it is anticipated to have a direct correlation with EI and an indirect association with RTP and EI via ATE. This leads us to postulate the following:

H1. 

Risk-taking propensity (RTP) has a significant positive effect on attitudes toward entrepreneurship (ATE).

H2. 

Risk-taking propensity (RTP) has a significant positive effect on entrepreneurship intention (EI).

H3. 

Attitude toward Entrepreneurship (ATE) has a significant positive effect on entrepreneurship intention (EI).

H4. 

Risk-taking propensity (RTP) and entrepreneurship intention (EI) are mediated by attitudes toward entrepreneurship (ATE).

2.5. The Relationship between Entrepreneurship Education Support, Attitudes toward Entrepreneurship, and Entrepreneurship Intention

To foster an entrepreneurial mindset and spirit, entrepreneurship education is essential (Thompson and Kwong 2016). Moreover, there is a positive relationship between entrepreneurship education and attitudes toward entrepreneurship (Yung et al. 2023). The ultimate objective of entrepreneurial education is to ensure the change in students’ mindsets when it comes to innovation and risk taking in business ventures (Jones et al. 2014b). Furthermore, entrepreneurship education is expected to generate psychological outcomes that stimulate a shift in attitudes regarding the desire to launch a new business venture or the commitment to innovation within an established organization (Kyro 2008). A key factor in the shift from entrepreneurial intent to actual entrepreneurial behavior is entrepreneurship education (Jabid et al. 2023; Li et al. 2024). Moreover, individuals exposed to comprehensive entrepreneurship education programs are more likely to develop positive attitudes toward entrepreneurial activities compared to those without such exposure (Aliedan et al. 2022; Porfírio et al. 2023). On the other hand, research conducted by Tahir and Kutpudeen (2023) indicates that educational support has little impact on attitudes toward entrepreneurship. Moreover, few studies have shown that entrepreneurship education has a negative and insignificant effect on attitudes toward entrepreneurship (Goswami et al. 2024; Listyaningsih et al. 2023). Likewise, results from the research of first-year college students by Nabi et al. (2018) were mixed, with some students showing a decline in their aspirations to start their own businesses after receiving entrepreneurship courses (Nabi et al. 2018). However, several studies conducted in Saudi Arab and China found a direct and significant relationship between entrepreneurship education and the students’ entrepreneurship intention (Aliedan et al. 2022; Liu et al. 2019). On the other hand, Taiwanese students’ entrepreneurial intentions decreased slightly despite high satisfaction and learning efficacy in entrepreneurship education programs because they realized it was difficult to establish a business (Chen et al. 2015). The researchers can make the following hypotheses based on the discussion.

H5. 

Entrepreneurship education (EE) has a significant positive effect on attitudes toward entrepreneurship (ATE).

H6. 

Entrepreneurship education (EE) has a significant positive effect on entrepreneurship intention (EI).

H7. 

The relationship between entrepreneurship education (EE) and entrepreneurship intention (EI) is mediated by attitudes toward entrepreneurship (ATE).

2.6. The Relationship between Entrepreneurship Education Support, Subjective Norms, and Entrepreneurship Intention

There is a positive association between the influence of entrepreneurship education on subjective norms and the prevalence of entrepreneurship (Wijayati et al. 2021; Yung et al. 2023). People are more inclined to attribute good social impacts and encouragement to their surroundings when it comes to entrepreneurial activity if they receive significant support for entrepreneurship education (Nguyen et al. 2022). The relationship between subjective norms and the desire to start a business is in line with TPB. Sahut et al. (2015) verified that SN is substantially linked to EI. A substantial relationship between SN and EI was found among university students in Oman (Tahir and Kutpudeen 2023). This finding is also supported by other studies (Contreras-Barraza et al. 2022; Sampene et al. 2022; Tahir and Kutpudeen 2023). Some studies failed to find a relationship between SN and EI (Alzamel 2021; Azim and Islam 2022; Ng et al. 2021). Another research in the Kingdom of Saudi Arabia found that the relationship between EE and EI is mediated by subjective norms (Wasiq et al. 2023). This leads us to the following hypotheses:

H8. 

Entrepreneurship education (EE) has a significant positive effect on subjective norm (SN).

H9. 

Subjective norm (SN) has a significant positive effect on entrepreneurship intention (EI).

H10. 

The relationship between entrepreneurship education (EE) and entrepreneurship intention (EI) is mediated by subjective norm (SN).

2.7. The Relationship between Entrepreneurship Education Support, Perceived Behavioral Control, and Entrepreneurship Intention

Understanding how educational experiences can change individuals’ ideas about their competence to engage in entrepreneurial activities requires an examination of the relationship between entrepreneurship education and perceived behavioral control. Entrepreneurship education has a significant effect on individuals’ perceived behavioral control, which eventually boosts their entrepreneurial intention (Porfírio et al. 2023). A study carried out in the United Arab Emirates (UAE) found that perceived behavioral control has a direct positive effect on entrepreneurship intention (AI Saiqal et al. 2019). Moreover, perceived behavioral control is the main factor that determines the EI of Balkan students (Vasileiou et al. 2023). However, determinants, including perceived behavioral control, mediate its indirect impact on entrepreneurial inclination (Nguyen et al. 2021). Therefore, we suggest the following set of hypotheses:

H11. 

Entrepreneurship education (EE) has a significant positive effect on perceived behavioral control (PBC).

H12. 

The relationship between entrepreneurship education (EE) and entrepreneurship intention (EI) is mediated by perceived behavioral control (PBC).

2.8. The Relationship between Need for Achievement, Perceived Behavioral Control, and Entrepreneurship Intention

A study conducted in Indonesia found that there is a positive effect of the need for achievement on entrepreneurship (Ardianti et al. 2017). Several studies conducted in Nigeria, Ghana, Morocco, and India found the same result that the need for achievement has a positive relationship with entrepreneurship intention (Bouarir et al. 2023; Mahajan and Gupta 2018; Nunfam et al. 2022; Palladan and Ahmad 2021). Furthermore, the need for achievement has a positive relationship with perceived behavioral control (Karimi et al. 2017). A number of Vietnamese, Saudi, Omani, and Chilean authors have shown that PBC substantially boosts EI (Azim and Islam 2022; Contreras-Barraza et al. 2022; Doanh 2021; Tahir and Kutpudeen 2023). A study conducted in Turkey and Poland found that the relationship between need for achievement and entrepreneurship intention is mediated by perceived behavioral control (Bağış et al. 2023b).

H13. 

Need for achievement (NFA) has a significant positive effect on entrepreneurship intention (EI).

H14. 

Need for achievement (NFA) has a significant positive effect on perceived behavioral control (PBC).

H15. 

Perceivedbehavioral control (PBC) has a significant positive effect on entrepreneurship intention (EI).

H16. 

The relationship between need (NFA) for achievement and entrepreneurship intention (EI) is mediated by perceived behavioral control (PBC).

2.9. Proposed Research Model

On the basis of a review of the literature and theories, our research proposed a conceptual model for examining the aforementioned hypotheses. The model shown in Figure 1 connects RTP, EES, and NFA to EI via ATE, SN, and PBC.

3. Methodology of the Study

3.1. Sample and Data Collection

The researchers in this study used a cross-sectional survey strategy to conduct quantitative research. The rationale behind this method’s selection was the ease and rapidity with which it could gather data from geographically scattered individuals. Despite the question of generalizability, numerous researchers have documented using non-probability sampling methodologies to address the difficult nature of entrepreneurial discipline (Nowinski et al. 2019; Thompson 2009; Wilson et al. 2007). However, this study tried to minimize generalizability concerns by employing the homogeneous convenience sample technique. The data for this study came from undergraduate and graduate students from public and private universities in Bangladesh utilizing non-probability homogeneous convenience sampling instead of the more traditional convenience sampling method. One major benefit of homogeneous convenience sampling over traditional convenience sampling is the increased certainty it provides regarding the generalizability of study outcomes (Jager et al. 2017). Conventional sampling is neither limited nor focused on a particular population, whereas a homogeneous sample is restricted based on sociodemographic characteristics (Jager et al. 2017). To minimize problems with generalizability, data were also collected from eight divisional cities in Bangladesh: Dhaka, Chittagong, Rajshahi, Khulna, Barishal, Sylhet, Rangpur, and Mymensingh. Participation was entirely optional, and all data were anonymized. This study’s data came from an online survey (Google form) that was sent out to university students in Bangladesh between 1 December 2023 and 31 January 2024. A total of 407 students provided responses; however, those replies lacking the necessary details were subsequently removed. After all the data were cleaned up, the study’s final data set included 381 individuals. The participants’ descriptive measures are displayed in

Table 1. Respondents’ profiles and characteristics.

Attributes	Characteristics	Frequency	Percentage
Gender	Male	224	58.8
	Female	157	41.2
Age of Respondents	Between 18 and 24	342	90
	Between 25 and 29	32	8
	Above 30	7	2
Background of Studies	Business and Management	264	69.3
	Arts and Social Sciences	73	19.2
	Others	44	11.5
Entrepreneurial Family Background	Yes	137	36
	No	244	64
Entrepreneurial Experience	Yes	104	27.3
	No	277	72.7
Previous Job Experience	Yes	95	24.9
	No	286	75.1
Area of Growing up	Urban Area	161	42.3
	Suburban Area	60	15.7
	Rural Area	160	42

.

3.2. Instruments Development and Data Analysis

Attitudes toward entrepreneurship (Liñán and Chen 2009; Thelken and de Jong 2020; Vuorio et al. 2018), subjective norms (Liñán and Chen 2009; Vuorio et al. 2018), perceived behavioral control (Liñán and Chen 2009; Thelken and de Jong 2020), risk-taking propensity (Farrukh et al. 2018; Fatoki 2020; Popescu et al. 2016), entrepreneurial intention (González-López et al. 2019; Liñán and Chen 2009; Thompson 2009), entrepreneurship education support (Denanyoh et al. 2015; Maheshwari and Kha 2022), and need for achievement (Bağış et al. 2023a) were utilized as instruments in this work. The authors evaluated the interrelationships of the variables by use of Structural Equation Modeling Partial Least Squares (SEM-PLS) with SmartPLS (v4.1.0.0). To determine the study significance level, the bootstrapping function (5000 resample) was employed. Evaluation of the measurement model (outer model), evaluation of the structural model (inner model), goodness-of-fit estimation (GoF), and hypothesis testing are the four steps that make up the SEM-PLS in this study (Hair et al. 2022). Every construct is evaluated using a 5-point Likert scale, with 1 representing strongly disagree, 2 representing disagree, 3 representing neutral, 4 representing agree, and 5 representing strongly agree, in ascending order.

4. Results and Analysis

4.1. Measurement Model Assessment

Construct Reliability and Validity

The measurement model of this study was analyzed using PLS-SEM.

Table 2. Evaluation of measurement model (reliability and validity and VIF).

Variables	Items	Loading	Cronbach’s Alpha	Composite Reliability (rho_a)	Composite Reliability (rho_c)	Average Variance Extracted (AVE)	VIF
ATE	ATE1	0.654	0.847	0.856	0.891	0.623	1.358
	ATE2	0.835					2.088
	ATE3	0.794					1.858
	ATE4	0.856					2.369
	ATE5	0.792					1.846
EES	EES1	0.906	0.893	0.898	0.933	0.823	2.435
	EES2	0.915					2.927
	EES3	0.901					2.717
EI	EI1	0.799	0.913	0.914	0.933	0.698	2.125
	EI2	0.826					2.399
	EI3	0.866					2.795
	EI4	0.848					2.672
	EI5	0.833					2.633
	EI6	0.840					2.847
NFA	NFA1	0.824	0.784	0.797	0.861	0.609	1.706
	NFA2	0.711					1.436
	NFA3	0.841					1.896
	NFA4	0.737					1.535
PBC	PBC1	0.677	0.803	0.805	0.859	0.505	1.473
	PBC2	0.705					1.628
	PBC3	0.755					1.735
	PBC4	0.755					1.61
	PBC5	0.719					1.507
	PBC6	0.647					1.334
RTP	RTP1	0.824	0.885	0.890	0.912	0.635	2.294
	RTP2	0.828					2.347
	RTP3	0.78					1.83
	RTP4	0.783					2.001
	RTP5	0.789					2.101
	RTP6	0.776					1.934
SN	SN1	0.761	0.794	0.796	0.859	0.549	1.579
	SN2	0.805					2.118
	SN3	0.752					1.885
	SN4	0.679					1.369
	SN5	0.702					1.335

shows the results of tests that looked at the reliability of factor loading (Cronbach’s alpha), composite reliability, average variance extraction (AVE), and convergent validity. Results with a composite reliability score and Cronbach’s alpha greater than 0.7 are considered reliable (Hair et al. 2017). There are seven constructs in this study, and all of them have Cronbach’s alpha scores above 0.75, which means that all of them meet the reliability requirement. Average Variance Extracted (AVE) was used as a method to measure convergent validity. If the AVE number is at least 0.5, there is enough convergent validity (Hair et al. 2014). There is sufficient convergent validity for all the variables examined in this study because their AVE values are all above 0.5. The structural model does not exhibit multicollinearity or negative effects between items or predictors, as indicated by the variance inflation factor (VIF) values ranging from 1.334 to 2.927 for each item, which is lower than the threshold value of 5.0 (Hair et al. 2017). Consequently, there is sufficient discriminant validity, and each construct is statistically unique.

Two methods were used to look at discriminant validity. The first used Fornell and Larcker’s criterion, which says that a test is discriminant when the square root of the AVE values of two different constructs is higher than the correlation between those constructs (Fornell and Larcker 1981). The model’s discriminant validity, as measured by the Fornell–Larcker criteria and Heterotrait–Monotrait (HTMT), is shown in

Table 3. Discriminant validity (Fornell–Larcker and HTMT criterion).

Discriminant validity (Fornell–Larcker Criteria)
	ATE	EES	EI	NFC	PBC	RTP	SN
ATE	0.790
EES	0.302	0.907
EI	0.631	0.372	0.836
NFA	0.455	0.281	0.499	0.780
PBC	0.422	0.370	0.611	0.371	0.711
RTP	0.481	0.354	0.648	0.563	0.487	0.797
SN	0.523	0.423	0.403	0.323	0.374	0.358	0.741
Discriminant validity (HTMT)
EES	0.345
EI	0.712	0.409
NFA	0.551	0.334	0.582
PBC	0.507	0.439	0.71	0.462
RTP	0.557	0.394	0.711	0.678	0.569
SN	0.626	0.495	0.463	0.404	0.462	0.423

Note: the bold parts are the thresholds to compare.

. Heterotrait–Monotrait (HTMT) ratios were employed in the second approach, which ensured discriminant validity up to the upper limit of 0.90 as an acceptable threshold (Hair et al. 2017; Henseler et al. 2015). Table 3 also displays the results of the HTMT criteria for measuring the model’s discriminant validity.

4.2. Common Method Bias or Variance

When the same individual provides responses for both the independent and dependent variables in the same study, using the same item context and comparable item attributes, common method bias is likely to be present. It is possible to identify common method bias in several ways. For instance, the unmeasured latent approach, the marker variable method, the full collinearity test, and Harman’s single-factor methods. Here, two strategies were employed by the researchers to identify this bias. One common and easy way to detect CMV statistically is with Harman’s single-factor test (Fuller et al. 2016). The fundamental concept is that in the event of the existence of CMV, a single component will be responsible for over 50% of the covariance between the criterion constructs and the items (Podsakoff et al. 2003). In this case, researchers found the value is 34.020%, which is less than the threshold limit, and we can say there is no common method bias in our study. The full collinearity test (VIF) was also used by the researchers to check for the common method bias. A dummy random variable was introduced by the researchers to accomplish this method. Usually, an inner model VIF larger than 3.3 is considered to indicate that the model might be polluted by common method bias. Accordingly, the model can be said to be free of common method bias if all VIFs in the inner model that come from a full collinearity test are less than or equal to 3.3 (Kock 2015; Kock and Lynn 2012). In our case, all VIF values are below 3.30, as shown in

Table 4. Full collinearity test (VIF) to examine common method bias.

	VIF
ATE→RV	1.327
EES→RV	1.103
EI→RV	1.036
NFA→RV	1.145
PBC→RV	1.027
RTP→RV	1.094
SN→RV	1.198

Note: RV: random variable, ATE: attitudes toward entrepreneurship; EI: entrepreneurship intention; EES: entrepreneurship education support; PBC: perceived behavioral control; SN: subjective norm; NFA: need for achievement; RTP: risk-taking propensity.

. Therefore, the researchers can assert that this model does not have any common method bias.

4.3. Structural Path Model Analysis to Examine Hypothesized Relationships

Researchers proceeded to the second step of model assessment following the assessment of the measurement model. The structural model was evaluated using the bootstrapping technique. This technique analyzes the relevance of indicators using factor loadings and estimates the model using parameter estimates and confidence intervals (Hair et al. 2022). The structural model is assessed using the determination coefficient (R²) and the Q² statistics. With values between 0 and 1, R² indicates the model’s predictive accuracy. To determine the model’s power, researchers calculated R squared, which shows that the exogenous variables ATE, PBC, SN, and EI each contribute 0.251, 0.214, 0.179, and 0.624 percent to the total variance, respectively (

Table 5. Coefficient of determination R².

	R-Square	R-Square Adjusted
ATE	0.251	0.247
EI	0.624	0.618
PBC	0.214	0.210
SN	0.179	0.177

). Values of Q² greater than 0 show that the model is predictively relevant (Hair et al. 2022); the ATE construct (0.237), entrepreneurial intention (0.446), PBC (0.201), and SN (0.17) all fall inside their respective parameters.

The path coefficients are significant for the relationships between RTP and ATE and RTP and EI at β = 0.428, p < 0.01, and β = 0.302, p < 0.01, respectively; therefore, H1 and H2 are supported. The path coefficient is also significant for the relationships between ATE and EI at β = 0.334, p < 0.01; therefore, H3 is supported. The path coefficients are significant for the relationships between EES and ATE and EES and SN at β = 0.15, p < 0.01, and β = 0.423, p < 0.01, respectively; therefore, H5 and H8 are supported. H11, H14, and H15 are also supported, as the path coefficients of the relationships between EES and PBC, NFA and PBC, and PBC with EI are significant at β = 0.228, p < 0.01; β = 0.29, p < 0.01; and β = 0.292, p < 0.01, respectively. However, H6, H9, and H13 are not supported, as the path coefficients for the relationship between EES and EI and SN and EI and the relationship between NFA and EI are at β = 0.052, p > 0.05; β = −0.0328, p > 0.05; and β = 0.065, p > 0.05, respectively.

Table 6. Results of hypothesis testing via bootstrapping.

HN	Path	Path Coefficient	t Value	p Value	2.50%	97.50%	Decision
H1	RTP→ATE	0.428	7.974	0.000 **	0.318	0.528	Supported
H2	RTP→EI	0.302	5.096	0.000 **	0.189	0.422	Supported
H3	ATE→EI	0.334	6.847	0.000 **	0.237	0.428	Supported
H5	EES→ATE	0.151	2.891	0.004 **	0.049	0.254	Supported
H6	EES→EI	0.052	1.428	0.153	−0.015	0.127	Not Supported
H8	EES→SN	0.423	8.224	0.000 **	0.313	0.516	Supported
H9	SN→EI	−0.032	0.761	0.447	−0.112	0.052	Not Supported
H11	EES→PBC	0.288	5.679	0.000 **	0.185	0.385	Supported
H13	NFA→EI	0.065	1.325	0.185	−0.027	0.164	Not Supported
H14	NFA→PBC	0.290	5.270	0.000 **	0.175	0.391	Supported
H15	PBC→EI	0.292	6.288	0.000 **	0.201	0.381	Supported

Note: For two-tailed experiments, statistical significance is described as p < 0.05 (for t value > 1.960). ** variable is at the 0.01 level (2-tailed). ATE: attitudes toward entrepreneurship; EI: entrepreneurship intention; EES: entrepreneurship education support; PBC: perceived behavioral control; SN: subjective norm; NFA: need for achievement; RTP: risk-taking propensity.

and Figure 2 depict the overall structural model analysis.

To assess the mediation effect of the variables, this study followed the procedures recommended by Hair et al. (2017).

Table 7. Result of mediation analysis.

HN	Mediation Effect	β Coefficient	t Statistics	p Values	2.50%	97.50%	Decision
H7	EES→ATE→EI	0.050	2.537	0.011 *	0.017	0.096	Full mediation
H16	NFA→PBC→EI	0.085	4.099	0.000 **	0.048	0.129	Full mediation
H4	RTP→ATE→EI	0.143	5.070	0.000 **	0.092	0.199	Partial mediation
H12	EES→PBC→EI	0.084	4.173	0.000 **	0.05	0.129	Full mediation
H10	EES→SN→EI	-0.013	0.753	0.451	−0.048	0.022	No mediation

Note: For two-tailed experiments, statistical significance is described as p < 0.05 (for t value > 1.960). * Variable is significant at the 0.05 level, and ** variable is at the 0.01 level (2-tailed).

shows that two variables (ATE and PBC) of TPB fully mediate the relationship between entrepreneurial education support (EES) and entrepreneurship intention (EI) and the relationship between need for achievement (NFA) and entrepreneurship intention (EI). The results in Table 7 indicate that ATE (β = 0.05, p < 0.05) mediated the relationship between EES and EI. PBC (β = 0.085, p < 0.01) and fully mediated the relationship between NFA and EI. ATE (β = 0.143, p < 0.01) and PBC (β = 0.084, p < 0.01) also partially mediated the relationship between RTP and EI and ESS and EI. However, SN (β = −0.013, p > 0.05) does not have any mediating effect between the relationship of ESS and EI. Apart from H10, all the mediating hypotheses (H7, H16, H4, and H12) are supported.

5. Discussion

In the current study, the researchers investigated how a student’s entrepreneurial cognitive condition is influenced by risk-taking propensity (RTP), entrepreneurship education support (EES), and need for achievement (NFA) in relation to the intention to start a new business venture in Bangladesh. Moreover, the researchers also investigated the mediating effect of the theory of planned behavior (TPB) in the link between risk-taking propensity (RTP), entrepreneurship education support (EES), need for achievement (NFA), and entrepreneurship intention (EI). Participants in the research were undergraduate and graduate students enrolled in public and private universities in Bangladesh. Following a discussion of the study’s contributions, the results indicate that TPB components (except subjective norms) and risk-taking propensity have a significant direct impact on the EI of the students in Bangladesh.

The main goal of this study was to find out if there was a direct link between RTP on ATE and EI. The results of the study show that there is a direct link between RTP on ATE and EI. Nevertheless, RTP had a more significant favorable effect on ATE (β = 0.292) than EI (β = 0.186). Our finding is supported by several previous studies (Hossain et al. 2019; Uddin and Bose 2012). It is clear that the individual who has a high risk-taking propensity has a more positive attitude toward entrepreneurship (Ahmed et al. 2021). Importantly, ATE mediates the connection between RTP and EI, which is an indirect interaction between RTP and EI. Therefore, students’ risk-taking intentions increase their favorable attitudes toward entrepreneurship, which in turn boosts their intention to establish their own venture in Bangladesh. Previous research that suggests ATE moderated the relationship between RTP and EI is consistent with our results (Farrukh et al. 2018; Munir et al. 2019).

The subsequent objective of this research endeavor was to ascertain whether EES has a direct effect on EI, ATE, SN, and PBC. The study’s findings point to a direct link of EES with ATE, SN, and PBC. The effect of EES on SN (β = 0.423) was much stronger than those of ATE (β = 0.302) and PBC (β = 0.288). This result fits with what Yousaf et al. found in their study (Qudsia Yousaf et al. 2022). The basic reasoning is that EES provides students with the skills and knowledge they need to focus on their career paths, cultivate positive attitudes and spirits toward starting new ventures, and acquire the necessary skills and abilities (Kaur and Chawla 2023; Nicolás et al. 2018). Moreover, people are more inclined to attribute positive social impacts and encouragement to their surroundings when it comes to entrepreneurial activity if they receive significant support for entrepreneurship education (Nguyen et al. 2022). Entrepreneurship education has a crucial effect on individuals’ perceived behavioral control, which eventually boosts their entrepreneurial intention (Porfírio et al. 2023). Nevertheless, this study’s findings suggest that EES does not have a direct effect on students’ entrepreneurship intention. Our finding is supported by previous studies (Maheshwari and Kha 2022). On the other hand, our results do not agree with the results reported by Hossain et al. (2019) and Kanur Chawla et al. 2023. ATE and PBC fully mediate the link between EES and EI. It can be argued that EES has an indirect impact on EI by enhancing an individual’s attitude toward entrepreneurship (ATE) and perceived behavioral control (PBC). Previous findings are also consistent with our findings (Nguyen et al. 2022). However, the relationship between EES and EI cannot be mediated via SN. It shows that university students in Bangladesh are not influenced by their social circles when deciding to start their own businesses. This trend could be a result of young people being more encouraged to follow their own passions and follow their dreams in the workplace, which is contributing to a more individualistic family dynamic.

Looking for a direct association between NFA, EI, and PBC was another goal of this research. In this study, researchers found that NFA and PBC are directly related. Similar results have been found in other studies (Karimi et al. 2017; Volery et al. 2013), which suggest that individuals with a strong desire to succeed frequently have high levels of self-efficacy and confidence. This confidence strengthens their perceived behavioral control because they believe they have the abilities and resources to achieve their goals, increasing their overall sense of control. The researchers did not find any direct relationship between NFA and EI. The probable reason may be that high-achieving individuals may actively seek and respond to feedback. Here, perceived behavioral control may be the feedback loop in which ambitious people evaluate and alter their entrepreneurial intentions based on feedback. Our finding is inconsistent with research conducted in Nigeria, Ghana, Morocco, and India that found a positive relationship between need for achievement and entrepreneurship intention (Bouarir et al. 2023; Mahajan and Gupta 2018; Nunfam et al. 2022; Palladan and Ahmad 2021). However, if PBC acts as a full mediator, the connection between NFA and EI becomes significantly stronger. Our finding is similar to a study conducted in Turkey and Poland that found that the relationship between need for achievement and entrepreneurship intention is mediated by perceived behavioral control (Bağış et al. 2023b). It may be that high-achieving people are self-confident. Since they believe they have the skills and resources to achieve their goals, this confidence boosts their perceived behavioral control and ultimately increases their entrepreneurial intention.

At last, the researchers examined the impact of ATE, SN, and PBC on EI. The findings point to a positive association between ATE and EI. Our result is also supported by previous studies that suggest that ATE consistently boosts EI (Anjum et al. 2021; Ellahi et al. 2021). In addition, PBC significantly improves EI. Our finding is similar to the previous research findings (Contreras-Barraza et al. 2022; Doanh 2021; Ellahi et al. 2021; Vasileiou et al. 2023). Researchers were surprised to find no significant effect between SN and EI. However, our findings are consistent with studies that failed to find a relationship between SN and EI (Alzamel 2021; Azim and Islam 2022; Ng et al. 2021). This trend might be due to the increasing degree of individualism in modern families, as young people are increasingly driven to pursue their own interests and desires in their careers.

6. Contribution, Limitations, and Future Research

6.1. Theoretical Contribution

Insights from this study have broad significance for a range of stakeholders, such as educators, policy makers, and those working to shape the entrepreneurial ecosystem specifically for emerging countries. Moreover, this study’s results provide important information for designing interventions and programs to help university students in Bangladesh become more entrepreneurial. To the best of our knowledge, this is the first study in Bangladesh to look at the mediation effect of the TBP construct on the relationship between risk-taking propensity, entrepreneurial education support, and the need for achievement on EI. The findings of our empirical study show that in Bangladesh, ATE and PBC are crucial intermediaries between RTP, EES, and NFA in shaping students’ entrepreneurial intentions. This study concludes that university-based entrepreneurial education has the potential to significantly impact the next generation’s entrepreneurial endeavors by fostering the development of students’ positive attitudes, subjective norms, and perceived control behaviors. On the other hand, students’ entrepreneurial intentions can be better understood by looking at their personality features. Moreover, attitudes and intentions toward entrepreneurship are positively impacted by a risk-taking tendency characteristic.

Although the idea of entrepreneurship is well known, most of the research on the topic has focused on developed nations with well-established entrepreneurial ecosystems. Academics and practitioners in a rapidly developing economy can benefit from this study since it aims to cover a knowledge gap in the field of entrepreneurship intention, entrepreneurship education, personality variables, and the TPB context. A few studies have demonstrated that entrepreneurship education positively affects students’ intentions to start their own businesses (Karmoker et al. 2020; Mensah et al. 2021; Porfírio et al. 2022; Rahaman et al. 2020b; Ramos et al. 2020), but only a small number of studies have examined the indirect relationship between EES and EI (Entrialgo and Iglesias 2016; Kaur and Chawla 2023; Li et al. 2023; Maheshwari and Kha 2022; Nguyen et al. 2022; Shah et al. 2020; Uddin et al. 2022). Moreover, there has been no research conducted to investigate the impact of EES, RTP, or NFA on EI, particularly in the context of emerging countries. Thus, this study adds to the current body of knowledge by providing empirical evidence of the three antecedents of TPB in the setting of Bangladesh that mediate the indirect relationship between entrepreneurial educational support, risk-taking propensity, need for achievement, and entrepreneurial intention.

6.2. Practical Implications

The study findings have several practical implications for educational institutions, policymakers, and the government. A positive relationship exists between entrepreneurial education and attitudes toward entrepreneurship, subjective norms, and perceived behavioral control. Therefore, the curriculum needs to be more business-oriented and practical in higher education programs. One way for universities to boost their students’ entrepreneurial spirit is by providing them with entrepreneurial education courses. However, universities should develop entrepreneurship education curriculums that are tailored to the cultural attributes of different countries, considering their specific settings and the requirements of their industries. To help students gain a more practical and relevant understanding of entrepreneurship, it could be helpful to incorporate real-world initiatives, mentorship opportunities, and practical experiences into the curriculum. Moreover, universities should provide students with hands-on experience in business startup and management to inspire them to pursue entrepreneurship as a career path. Students have a better chance of becoming entrepreneurs as they gain expertise in business and how to start their own companies (Shi et al. 2019). It is important to note that students’ personal attitudes, subjective norms, and perceived behavioral control are impacted by entrepreneurial education support. If universities organize business pitch competitions and other activities that apply what students learn to real-world situations, it will inspire students to become entrepreneurs and improve their attitudes toward entrepreneurship. That is why it is important for students to have the opportunity to work on research or spin-off initiatives while attending university. It is emphasized by Liao et al. (2022) that an entrepreneurial mindset is shaped through entrepreneurial education, and it is a key factor in motivating entrepreneurial intention. Universities should, therefore, provide students with the opportunities to launch their own businesses through business centers and incubators. Moreover, higher education institutions must work with industry to influence young people’s entrepreneurial intents and help them improve their skills and expertise. It is possible to enhance subjective norms by fostering a favorable perception of the function of entrepreneurship among all individuals. It is also important for policymakers to acknowledge that entrepreneurship is a key driver of economic growth and development. They should work to cultivate positive attitudes toward entrepreneurship, which can help spread knowledge about entrepreneurial orientation in a comprehensive way and create a thriving ecosystem for entrepreneurship. The study’s results can help policymakers measure and foster an entrepreneurial ecosystem that is more conducive to success.

6.3. Conclusion, Limitations, and Future Research

Economic growth and development are largely determined by a country’s entrepreneurial activities. Simply said, entrepreneurship has the potential to improve a nation’s economy by increasing employment opportunities. The aim of the study was to investigate how entrepreneurship education and personality traits have created an effect on the entrepreneurship intention of university students in Bangladesh and how the theory of planned behavior (TPB) mediates in this relationship. Results indicate that TPB components (except subjective norms) and risk-taking propensity have a significant direct impact on the EI of the students of Bangladesh.

Universities should be more focused on entrepreneurship education for the students. At the same time, universities should include modern entrepreneurship education learning in their curriculum that can boost the student’s entrepreneurship intention by creating a positive attitude toward entrepreneurship. Graduates who participate in entrepreneurial education programs have a better chance of becoming employers rather than employees, which would be an enormous boost to the nation’s long-term economic and social growth. Additionally, by teaching young people to be entrepreneurs, society can turn educated people from a social liability into a social asset that can make significant contributions to achieving inclusive and sustainable development goals. The government should support the universities to provide adequate funds for the proper implementation of the EE program.

In addition, our study sheds light on the specific educational, cultural, and social circumstances of Bangladesh, laying the groundwork for more precise interventions and policies. University students have the power to change the world, so it is critical that they should be part of an entrepreneurial ecosystem that encourages innovation, risk taking, and the integration of valuable entrepreneurship education. Our research has broad ramifications, and it is clear that entrepreneurship education programs trying to inspire university students to start their own businesses need to take all of these factors into account. Addressing risk perceptions, improving entrepreneurship education programs, and tapping into the natural desire for success can all help to create a more suitable atmosphere for the development of entrepreneurial aspirations. Moving forward, stakeholders, legislators, and educators should work together to develop and implement policies that will empower and inspire the next generation of entrepreneurs. This will facilitate the development of a more dynamic and robust entrepreneurial ecosystem. The findings of this study pave the way for more in-depth investigations and concrete programs to help universities unleash the entrepreneurial spirit of their students.

In addition to the contribution, this study raised several issues that need to be addressed in future studies. Two personality traits (risk-taking propensity and need for achievement) and entrepreneurial education support have been the exclusive focus of this study. However, other elements such as proactive personality, perceived creativity, moral obligation, and the environment of doing business may also influence students’ entrepreneurship intention. To further explore the relationship between these factors, it is recommended to employ a mixed-method or longitudinal strategy, as this study was quantitative in nature. Moreover, future research should focus on students from higher secondary levels to measure their entrepreneurship intention. Furthermore, future research can employ a multi-group analysis to compare students with and without work or entrepreneurial experience.