The impact of entrepreneurship on college students’ innovative and entrepreneurial behavior under the influence of corona virus disease 2019

This study investigates how COVID-19 pandemic has hindered the development of college students’ entrepreneurial skills. Focusing on three key traits-innovativeness, initiative, and risk-taking-this study applies cognitive-behavioral theory to analyze their impact on entrepreneurial willingness. Additionally, it evaluates the strength of this relationship by measuring how entrepreneurial spirit shapes intent. Key findings reveal varying effects across disciplines: major-specific differences in entrepreneurial intention (EI), innovation, initiative, and risk-taking scored 6.829, 1.718, 4.909, and 5.883, respectively. There is no significant connection between professionalism and innovativeness. Strong correlations emerged between environmental factors and entrepreneurial traits-initiative (0.659, p < 0.01), innovation (0.784, p < 0.01), risk-taking (0.677, p < 0.01), and willingness (0.643, p < 0.01). Among these, initiative and risk-taking exerted the greatest influence on willingness. Correlation analysis further confirmed entrepreneurship’s positive, statistically significant role in predicting intent. College students’ entrepreneurial willingness will therefore be enhanced by promoting entrepreneurship courses in institutions of higher learning to complement the development of an entrepreneurial spirit (ES).

1 Introduction

1.1 Background

Corona Virus Disease (COVID)-19 pandemic has disrupted China’s economy, slowed its growth and reshaped the entrepreneurial landscape. As a result, college graduates now face unprecedented job market challenges (García-Guerrero and Beltrán-Sánchez, 2021). From a human capital and opportunity-based entrepreneurship perspective, economic shocks intensify uncertainty while simultaneously generating new market gaps that require adaptive entrepreneurial cognition and behavior (Shepherd, 2020). “China’s ‘mass entrepreneurship and innovation’ policy promotes student startups but empirical research shows that the actual success rates among student-led ventures remain very low (Li et al., 2019). Several barriers contribute to this low success rate. Many students lack critical resources-startup capital, managerial skills, and industry experience-leaving them ill-equipped to navigate the complexities of entrepreneurship. According to Social Cognitive Theory, entrepreneurial behavior is not solely driven by opportunity availability but by self-efficacy beliefs and outcome expectations that shape intention and persistence under risk (Bandura, 2001; Newman et al., 2019). Without addressing these gaps, even the most motivated graduates struggle to turn their ambitions into viable businesses.

Research confirms that entrepreneurial spirit (ES) functions as a core psychological and behavioral resource underlying entrepreneurial intention (EI). While numerous studies have examined how to boost entrepreneurial skills among college students, few have specifically analyzed how to enhance the quality of entrepreneurial education through the lens of entrepreneurship itself. Most existing research treats entrepreneurship as a broad, undifferentiated concept. However, it still needs deeper investigation into whether and how different dimensions of entrepreneurship (such as innovativeness, risk-taking, and initiative) distinctly influence students’ entrepreneurial intention (EI). This gap in the literature points to an important area for further exploration.

Research consistently demonstrates that ES serves as a critical determinant in shaping college students’ EI and subsequent venture success. While extant literature has extensively examined skill development and attitude formation in student entrepreneurship (Nabi et al., 2017), insufficient attention has been paid to how distinct entrepreneurial dimensions-particularly innovativeness, proactiveness, and risk propensity-differentially influence intention formation (Liu et al., 2021). Current scholarship predominantly conceptualizes entrepreneurship as a unitary construct (Karimi, 2020), overlooking the need for granular analysis of how its fundamental components interact to predict entrepreneurial willingness. This oversight represents a significant theoretical gap, particularly given the varying predictive power these dimensions may exert on students’ entrepreneurial decision-making processes. From the perspective of cognitive-behavioral theory, such aggregation weakens explanatory precision because different entrepreneurial traits activate different cognitive mechanisms such as opportunity scanning, action initiation, and loss tolerance (Newman et al., 2019).

This study comprehensively analyses the entrepreneurship and its relationship with entrepreneurial willingness, with particular focus on the key determinants that shape college students’ EI. Through empirical analysis, it identifies and evaluates the specific factors that most significantly influence students’ entrepreneurial decision-making processes. A global survey targets college students to explore their entrepreneurial behaviors and intentions. It systematically examines how three key dimensions of entrepreneurship affect these intentions. Hypotheses are developed and tested to offer insights for future research on college student entrepreneurship education.

2 Literature review

Researchers began studying entrepreneurial ability earlier. In the 1970s and 1980s, entrepreneurship education courses first emerged in the United States. Babson College is a great example of a school that offers such education. The main goal of this college is to help students build the skills they need to start new businesses. It does this through programs like the China Entrepreneurship Observation Program.

Scholars have delved deeply into what makes up entrepreneurial ability. Many studies suggest that top-notch entrepreneurs possess a wide range of skills. These skills are mainly shown in areas like management, organization, interpersonal relations, and technical skill. In other words, entrepreneurs are jacks-of-all-trades (Alsafadi et al., 2020). In China, researchers have carried out a lot of practical studies on college students’ innovation and entrepreneurship education (IEE) as well as their entrepreneurial capabilities. These studies show that IEE is on the right track, and students generally have good abilities in these fields. But there are still some problems that have not been solved yet. For example, people need to improve the IEE system, strengthen the teaching faculty, and come up with new educational methods and tools (Liu R. et al., 2021; Liu Y. et al., 2021). From an entrepreneurial cognition perspective, these weaknesses constrain the development of self-regulatory and opportunity-evaluation skills that are critical for intention formation and action execution (Newman et al., 2019). One of the most important areas of research on college students’ IEE is the development of their innovative and entrepreneurial skills. Most academics base their studies on the situation and issues facing this type of instruction. They suggest training strategies, concepts, and models for certain student groups based on pertinent theories. Additionally, they propose methods and ideas to improve the current model of IEE (Yang and Ji, 2021; Liu R. et al., 2021; Liu Y. et al., 2021).

Currently, there is not a unified national model for innovation and entrepreneurship training. Most of the existing approaches focus on specific groups, like students majoring in business or engineering. Most researchers have a narrow scope for their studies. They mainly look at entrepreneurship education from external viewpoints, rather than from the entrepreneurs’ own shoes. There are very few studies that try to understand the issue from the entrepreneurs’ perspective. Additionally, when it comes to college students’ EI, research from an entrepreneurial perspective is also limited.

2.1 Overview of relevant theories and design of survey process

2.1.1 Overview of entrepreneurship research

2.1.1.1 Connotation of ES

Entrepreneurship relies heavily on collective creativity, with team innovation being particularly crucial. Finding and seizing previously undiscovered market possibilities is the goal of launching a firm. It involves creatively arranging and combining the initial production factors and resource distribution. By launching new products or services, expanding into new markets, and attracting and obtaining new customers, organizational performance gets better over time (Chen et al., 2019; Chen, 2019; Nunfam et al., 2021).

Entrepreneurial characteristics consist of being proactive, willing to take risks, innovative, and having an enterprising mindset. Research by Zhang et al. (2021) shows that entrepreneurship is positively linked to the returns, growth, and risks involved in the performance of new businesses. Entrepreneurship is an ongoing process of using and transforming resources. It adapts to changing external circumstances over time. Through entrepreneurship, a company can bring together internal and external resources, which helps it develop a unique competitive edge. From an ecosystem perspective, supportive national systems lower opportunity costs and enhance entrepreneurial self-efficacy through access to finance, infrastructure, and regulatory legitimacy (Bischoff et al., 2018).

Figure 1 demonstrates that entrepreneurship serves as a subjective spiritual force. It acts as the driving source for the existence of entrepreneurs. The subjectivity of individuals originates from their innate independent spirits and self-disciplined personality traits. This subjectivity has the power to direct human activities. And this principle is also essential for the development of entrepreneurship.

Figure 1

Figure 1. Three characteristics of entrepreneurship.

Institutional aspects matter a lot for entrepreneurship. The development of entrepreneurship does not happen in a vacuum. It goes hand in hand with changes in the outside political system and economic situation. The social environment where entrepreneurship takes place has a big impact on it. As a result, entrepreneurship develops with certain institutional features. On top of that, a great national system that encourages entrepreneurship, along with smart strategies for building up the external environment, can really help it grow. When the government offers good incentives like financial support or easier regulations, and works on improving things like infrastructure and market access, more people are likely to start and run businesses successfully.

Inheritance is everywhere in society. The historical periods we live in today are a result of carrying forward the experiences of those who came before us. When it comes to entrepreneurs, while skills, qualities, and talents aren’t passed down in a traditional sense, the ES can be. Both inheritance and future development are possible for this spirit. Through long-term accumulation and company operations, entrepreneurship has been passed on and developed over time as a crucial component of corporate culture. Additionally, it has emerged as a new tenet for enhancing the cultural and economic landscape (Zhong et al., 2020; Ziyae and Sadeghi, 2020).

2.1.1.2 Entrepreneurship measurement

New businesses rely heavily on entrepreneurship for growth and development. People can reasonably believe that at the heart of it, all entrepreneurial groups possess a common entrepreneurial mindset and set of values. You can see these traits reflected in the actions and operations of individual entrepreneurs and their companies. Entrepreneurship is primarily characterized by three crucial elements: innovation, initiative, and a readiness to take risks. As illustrated in Figure 2, these distinct dimensions are explained, along with their significance within the realm of entrepreneurship.

Figure 2

Figure 2. Entrepreneurship dimension and its connotation.

2.2 Overview of entrepreneurial willingness

The study of EI has its roots in theories about individual behavioral traits. In psychology, this includes cognitive-behavioral theory, social cognitive theory, and cognitive psychology. Social cognitive theory is made up of three main components: the ternary interaction theory, the self-efficacy theory, and the observational learning theory (Cattaneo et al., 2018). They depend on each other and can boost one another. The idea of ternary interactive determinism offers some theoretical support for researching EI.

Furthermore, entrepreneurial skills influence college students’ drive to launch a business. Some scholars break down college students’ entrepreneurial skills into eight areas: innovation ability, social skills, strategic thinking, self-discipline, commitment, risk-taking capacity, teamwork skills, and the ability to learn. Studies show that college students’ abilities in risk-taking, innovation, strategic thinking, social interaction, self-control, teamwork, and commitment have a strong positive connection with their desire to start a business (Shen et al., 2019; Portuguez Castro and Gómez Zermeño, 2021). From a psychological mechanism perspective, these competencies function by enhancing students perceived behavioral control and adaptive opportunity schemas, which directly influence intention formation.

The development of the desire to start a business is a complicated and ever-changing process. However, this study can group the things that affect college students’ urge to become entrepreneurs into four main types. In Figure 3, these are the important elements that mold college students’ intention to start a business.

Figure 3

Figure 3. Influencing factors of college students’ EI.

3 Methods

This study thoroughly explores the impact of three fundamental elements of entrepreneurial spirit—innovation, proactiveness, and risk-taking—on the initial entrepreneurial intentions (EI) of college students. A quantitative study methodology was utilized, incorporating a structured questionnaire derived from established and tested measuring scales to guarantee methodological rigor.

Descriptive statistics, t-tests, one-way ANOVA, and correlation analysis were used to look at the data. We used these methods to talk about the features of the respondents, find disparities between groups, and look at how the major factors are related to each other. Cronbach’s α and test–retest procedures were used to check for reliability, while Confirmatory Factor Analysis (CFA) was used to check for construct validity. We utilized the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity to see if the data were good for factor analysis.

The research concentrates on five principal variables: social environment, proactiveness, creativity, risk-taking, and emotional intelligence (EI). We conducted correlation analysis to evaluate the proposed hypotheses and learn more about the things that affect college students’ early entrepreneurial inclinations.

3.1 Questionnaire design and survey

Figure 4 presents the research route.

Figure 4

Figure 4. Research route.

The study’s target audience comprises college students worldwide who are exhibiting entrepreneurial interest. This include students with entrepreneurial ambitions, individuals who have engaged in entrepreneurship-related training, practical activities, or innovation and entrepreneurship contests. Defining this demographic delineates the scope of inference and enhances the generalizability of the findings.

The questionnaire was disseminated through two methods: (1) centralized, on-site distribution at selected colleges, and (2) an online survey platform. The instrument was modified from established validated scales to enhance clarity, precision, and contextual relevance. All items employed a 5-point Likert scale, with 1 signifying “strongly disagree” and 5 denoting “strongly agree” (Hatakeyama et al., 2022).

The questionnaire comprised a total of 50 items. Fourteen (14) items related to personal information, including details like gender, age, educational level, major subject, academic performance, place of birth, and the location of the college or university they attend. There are eight (8) items about risk-taking behaviors, eight (8) items about innovation (invention), and eight (8) items about initiative-taking. Furthermore, there are six (6) aspects related to the external environment. These aspects cover elements like participation in entrepreneurship training programs, entrepreneurial. Moreover, there are six indicators used to measure EI. Altogether, the questionnaire comprises a total of 50 questions.

A total of 550 questionnaires were disseminated, and 535 were retrieved. Following the elimination of partial or incorrect responses, 521 valid questionnaires were preserved, yielding an effective response rate of 94.73%.

A descriptive analysis was performed to summarize the demographic features of the respondents and to identify any confounding variables. T-tests and one-way ANOVA were employed to ascertain the presence of significant differences among demographic groups (Scorza et al., 2018).

Reliability testing encompassed Cronbach’s α for internal consistency and test–retest reliability to assess the stability of the questionnaire over time (Wang and Shafieezadeh, 2020). Construct validity was evaluated via Confirmatory Factor Analysis (CFA), corroborated by the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test to ensure the suitability of factor analysis for the dataset.

In Figure 5a, the α values associated with the five variables are 0.875, 0.806, 0.882, 0.865, and 0.846. It is worth emphasizing that each of these values exceeds 0.8. Moreover, the Cronbach’s α coefficient for the entire scale reaches a value of 0.957. Such a relatively high coefficient indicates a strong level of internal consistency, which means that the scale used in the study is highly reliable. Turning to Figure 5b, the KMO values for the five dimensions, namely EI, environmental factors, initiative, innovation, and risk-taking, are 0.847, 0.800, 0.885, 0.837, and 0.865, respectively. These KMO values, which are all quite substantial, imply that the data within these dimensions are suitable for factor analysis, as they suggest a good degree of correlation among the variables within each dimension.

Figure 5

Figure 5. Reliability and validity analysis. (a) Reliability test of latent variables; (b) KMO test results.

Principal component factor analysis is conducted for each of the five dimensions of the scale. Importantly, the probability of all the statistical values of the Bartlett test for the subscales is 0.000. It shows that there is a significant correlation among the variables within these subscales. Additionally, the KMO values of the subscales related to the five dimensions, that is, EI, environmental factors, initiative, innovation, and risk-taking, are 0.847, 0.800, 0.885, 0.837, and 0.865, respectively. These relatively high KMO values suggest that in terms of problem selection, these dimensions are highly interrelated. In other words, they are less likely to cause confusion or ambiguity, which validates the suitability of using factor analysis for these dimensions and the overall reliability of the scale in representing the relevant concepts.

The KMO test is used to assess whether the data is suitable for factor analysis. The KMO statistic ranges from 0 to 1. Larger values of this statistic indicate stronger relationships among the variables. Specifically, when the sum of the squares of the simple correlation coefficients is significantly greater than the sum of the squares of the partial correlation coefficients, the KMO value approaches.

It indicates that the data are highly suitable for factor analysis. Otherwise, if the simple correlation coefficients are close to 0, the KMO value decreases, indicating weaker associations between the variables. Commonly recognized KMO benchmarks are as follows: >0.9 (the data is highly suitable for factor analysis), 0.8 (the data is suitable), 0.7 (considered acceptable), 0.6 (marginal suitability) and <0.5 (the data is unsuitable) (Sadowska et al., 2021; Mograbi et al., 2018).

The moderation effect test is shown in Equation 1:

$\begin{array}{ll}Y={\beta }_0+{\beta }_{1}X+{\beta }_{2}Z+{\beta }_{3}X\ast Z& (1)\end{array}$

𝛽₁ is the influence coefficient of 𝑋 on 𝑌. 𝛽₂ is the influence coefficient of 𝑍 on 𝑌. 𝛽₁ and 𝛽₂ reflect the size of the main effect. 𝛽₃ reflects the regulatory effect.

The moderating effect is tested using SPSS software. The observations of the independent and moderator variables are standardized (normalized) to reduce the problems associated with multicollinearity. Then, the elements of related variables are regressed to the dependent variables by applying the multi-level regression model (Peprah, 2019; Illia et al., 2018), as presented in Equation 2:

$\begin{array}{ll}Y={\beta }_0+{\beta }_{1}X+{\beta }_{2}Z+{\beta }_{3}X\ast Z& (2)\end{array}$

In Equation 2, the unnormalized values are X, Z, Y, and the normalized ones are 𝑋̅ and 𝑍̅.

Hypotheses have been formulated. These hypotheses are then verified by examining the relationship between college students’ entrepreneurship, its related dimensions, and EI (Mekyska et al., 2018). The detailed hypotheses are displayed in Table 1.

Table 1

Table 1. Hypotheses.

4 Results and discussion

4.1 Scale statistical analysis

4.1.1 Descriptive statistical analysis

The statistical analysis outcomes of the 521 questionnaires are illustrated in Figure 6. In Figure 6, the college students surveyed are mainly undergraduates within the age range of 18 to 23 years old, constituting 74.5% of the entire sample. The number of juniors and seniors is evenly distributed, whereas the percentage of graduate students is relatively low. Undergraduates represent the largest segment, making up 90.2% of the respondents. Among these undergraduate students, those majoring in science and engineering, humanities, and economics and management make up relatively higher percentages, which are 29.2, 14.2, and 39%, respectively. Students in other majors have a relatively low proportion. The distributions of all the surveyed students are normal. There is no skewed data.

Figure 6

Figure 6. Demographic characteristics of surveyed college students including (a) age distribution, (b) education level distribution, and (c) profession/academic major distribution.

This demographic composition aligns with prior large-scale studies on college students’ entrepreneurial intention, supporting the representativeness and reliability of the sample (Huang et al., 2021; Hardini and Taufiq, 2021). Beyond descriptive adequacy, this sample composition is particularly relevant given that early adulthood represents a critical developmental stage for entrepreneurial cognition and intention formation. Prior research indicates that entrepreneurial beliefs, self-efficacy, and behavioral orientations are especially malleable during undergraduate years, reinforcing the analytical value of the present findings (Krueger et al., 2000; Newman et al., 2019).

4.1.2 Statistical difference analysis

University majors are usually categorized into various broad disciplinary groups. These include science and engineering, social sciences, humanities, economics and management, agriculture/forestry/technology, medicine, military, law, and other fields. This classification is made according to the general characteristics of the subjects involved in entrepreneurship. Figure 7 showcases the three dimensions of entrepreneurship. It also provides an analysis of how these dimensions change across different major groupings. By doing so, it emphasizes the significant differences that exist among college students in relation to these aspects of entrepreneurship.

Figure 7

Figure 7. The three dimensions of entrepreneurship and the analysis of the differences between the majors of college students. (a) Difference analysis of initiative; (b) difference analysis of innovation; (c) difference analysis of risk-taking.

Figure 7 shows that undergraduate majors have varying impacts on different elements of the ES, such as innovation, the desire to start a business, being proactive, and the willingness to take risks. An analysis reveals that the difference in the main effect of innovation measures 1.718. Its significance level stands at 0.101, exceeding the typical 0.1 significance threshold. In other words, when looking at innovation as either a trait or an action, students from different undergraduate majors do not really show any notable differences. Instead, it is likely to be more significantly influenced by individual attributes or external circumstances rather than by the specific academic discipline in which students are enrolled. Earlier entrepreneurship education studies often assumed that students in business or engineering disciplines inherently possess stronger innovative capacities. However, the present findings challenge this implicit assumption, suggesting that innovation is not monopolized by any single academic field. This finding builds on previous studies by empirically distinguishing innovative potential from entrepreneurial behavior, thus elucidating discrepancies noted in earlier discipline-specific analyses (Liu R. et al., 2021; Liu Y. et al., 2021).

This finding is consistent with contemporary cognitive psychology research that defines creativity and innovative capacity as complex cognitive processes influenced chiefly by individual problem-solving approaches, intrinsic motivation, and previous learning experiences, rather than by disciplinary exposure (Ivcevic and Hoffmann, 2022; Zabelina and Ganis, 2018). From a cognitive-behavioral standpoint, innovation appears to function as a latent cognitive resource that requires behavioral and environmental activation to translate into entrepreneurial intention. This interpretation aligns with Ajzen’s (1991) Theory of Planned Behavior, which posits that cognitive attitudes alone are insufficient predictors of intention without supportive behavioral control and contextual reinforcement.

On the contrary, the differences in the main effects for entrepreneurial willingness (measured at 6.829), proactiveness (at 4.909), and risk-taking (at 5.883) all reach statistical significance. This suggests that the undergraduate major selection exerts a remarkable impact on students’ entrepreneurial behaviors and attitudes. Specifically, students majoring in economics and management, medical and military sciences, and law display more pronounced entrepreneurial inclinations. They also show a greater tendency to seize entrepreneurial opportunities and are more willing to embrace the risks inherent in entrepreneurial endeavors.

These findings extend Social Cognitive Theory by empirically illustrating how disciplinary learning environments shape behavioral dispositions through repeated exposure to decision-making under uncertainty, responsibility, and performance evaluation (Bandura, 1986). Prior studies have emphasized the importance of self-efficacy in entrepreneurial intention formation; the present study provides concrete evidence that academic contexts serve as mechanisms through which such self-efficacy is cultivated (Karlsson and Moberg, 2013; Newman et al., 2019).

Academic programs vary widely in the learning environments they create, the reinforcement structures they promote, and the behavioral models they expose students to. Majors such as business, law, and military science often emphasize decision-making under uncertainty, initiative-taking, and leadership—conditions that strengthen entrepreneurial self-efficacy and the perceived desirability of entrepreneurial behavior (Newman et al., 2019; Karlsson and Moberg, 2013). Thus, students internalize entrepreneurial norms differently depending on their disciplinary context. This study refines previous entrepreneurship research by demonstrating that academic major affects behavioral activation rather than innovation itself (Liu R. et al., 2021; Liu Y. et al., 2021).

These results suggest that although innovation appears to be a trait that is more evenly spread among college students across different majors, EI, proactiveness, and the inclination to take risks are distinctly influenced by the academic fields that students are enrolled in. This realization highlights the necessity of formulating entrepreneurial education strategies that are tailored to specific disciplines. For example, educational programs in the arts and humanities or engineering fields, which may not inherently cultivate a strong sense of EI or a willingness to take risks as prominently as some other disciplines, could greatly profit from targeted initiatives. These initiatives should be designed to deliberately nurture and develop these entrepreneurial qualities among students in a more focused manner.

In addition, educational institutions should think about carrying out comprehensive needs assessments within every academic department. By doing so, they can customize entrepreneurship education curriculums, making sure that students from all majors, not merely those in the fields typically associated with business, are given suitable chances to develop their entrepreneurial capabilities. These research outcomes also necessitate cross-disciplinary cooperation. For instance, incorporating entrepreneurship modules into courses outside of the business domain can expand students’ exposure to entrepreneurial concepts. This approach can further stimulate more inclusive participation in entrepreneurial projects, enabling students from diverse academic backgrounds to engage with and contribute to the entrepreneurial ecosystem.

This is in line with what Social Cognitive Theory’s focus on social modeling and observational. Being around successful entrepreneurs and doing real entrepreneurial tasks greatly boosts self-efficacy and perceived competence (Liguori et al., 2018; Bischoff et al., 2018). Such encounters can stimulate entrepreneurial cognitive frameworks, even in fields not conventionally associated with entrepreneurship.

Figure 8 displays the three aspects of entrepreneurship and shows how the analysis results differ based on whether college students have joined entrepreneurial competitions.

Figure 8

Figure 8. Difference analysis of whether college students have participated in entrepreneurship competitions. (a) Difference analysis of initiative; (b) difference analysis of innovation; (c) difference analysis of risk-taking.

In Figure 8, college students who participated in entrepreneurship competitions demonstrated remarkable strength in all areas of EI and spirit. Their performance varied based on how deeply they engaged with entrepreneurship-related activities. Indeed, the scores of these students were significantly higher than those of those who had not participated. Among the students surveyed, 59.7% had attended entrepreneurship lectures, 27% had received entrepreneurship education or training, and 26.3% had participated in entrepreneurship competitions.

This pattern is consistent with prior empirical and meta-analytic research indicating that experiential entrepreneurship education produces stronger effects on entrepreneurial intention than lecture-based instruction (Nabi et al., 2017; Rauch and Hulsink, 2015). This information reveals that various forms of entrepreneurship education, such as lectures, training activities, and competitions, have distinct effects on students’ entrepreneurial motivation and mindset. The problem is that most colleges and universities do not have a proper system to categorize these educational methods or combine them strategically. To fix this, schools need to base their entrepreneurship education programs on solid research. They should create well-organized plans to make sure these programs work as well as possible in developing students’ entrepreneurial qualities.

Participation in competitions is also confirmed by meta-analyses to produce stronger and more durable effects on entrepreneurial intention than lecture-based instruction (Nabi et al., 2017; Rauch and Hulsink, 2015). Entrepreneurship education and experiential activities have been shown to foster cognitive and psychological capacities—such as adaptive coping, resilience, and opportunity recognition—by enhancing individuals’ cognitive strategies, psychological capital, and entrepreneurial cognition, which aligns conceptually with cognitive-behavioral mechanisms (Fayolle and Gailly, 2015).

Social Cognitive Theory posits that people develop self-efficacy through mastery experiences and observing others, which influence their future behavior and goals. In the context of entrepreneurship education, practical activities such as competitions provide students with real-world problem-solving opportunities, expert feedback, and exposure to entrepreneurial role models—all of which align with Social Cognitive Theory’s sources of self-efficacy and can strengthen entrepreneurial self-efficacy. Research consistently shows that entrepreneurial self-efficacy is positively linked to entrepreneurial intentions, making it a strong predictor of EI (Newman et al., 2019; Santos and Liguori, 2020).

From a cognitive-behavioral perspective, participation in competitions facilitates the development of adaptive cognitive schemas related to opportunity recognition, resilience, and risk assessment among students. These activities are not only empirically effective but also endorsed within the established frameworks of entrepreneurship as a recognized academic discipline, thereby legitimizing the integration of experiential learning into curricula (Harrison, 2023). Competitions frequently replicate authentic entrepreneurial uncertainty, enabling students to engage in cognitive-behavioral coping strategies, including systematic problem-solving, reframing failures, and iterative learning—strategies that enhance emotional intelligence and entrepreneurial action.

4.2 Correlation analysis and hypothesis verification

To explore the relationship between the related dimensions of college students’ entrepreneurship and their EI, five variables namely the social environment, proactiveness, innovation, risk-taking propensity, and entrepreneurial aspiration are chosen for a correlation analysis. The details of this analysis are presented in Figure 9.

Figure 9

Figure 9. Correlation analysis between entrepreneurship dimensions and entrepreneurial intention. (a) Correlation between students’ entrepreneurial willingness and key entrepreneurial dimensions, including initiative, innovation, and risk-taking. (b) Correlation between entrepreneurial willingness and entrepreneurship projects under different social and environmental factors.

In Figure 9a, a significant positive correlation exists among environmental factors, initiative, innovation, risk-taking, and EI. The respective correlation coefficients are 0.659 (with p < 0.01), 0.784 (p < 0.01), 0.677 (p < 0.01), and 0.643 (p < 0.01). These results support the notion that the ES of college students has a positive association with their EI. In Figure 9b, on the x-axis, Q1 to Q7 refers to seven sub-items used to measure EI. When examining the relationships between these sub-items and the three aspects of the ES (initiative, innovation, and risk-taking), the correlation coefficients are 1.000, 0.780, 0.815, 0.735, 0.841, 0.764, and 0.784. All these coefficients are significant at the p < 0.01 level, clearly indicating a reliable connection.

These results clarify that proactiveness and risk-taking are stronger behavioral predictors of EI than innovation, suggesting a behavioral mediation pathway: innovation indirectly contributes to intention through proactive and risk-oriented behaviors (Ajzen, 1991; Krueger et al., 2000).

Students’ choice of majors has an impact on how proactive they are, their willingness to take risks, and their eagerness to start a business. This shows that the field of study really matters when it comes to forming entrepreneurial behaviors. Also, students who have taken part in things like entrepreneurship lectures, training sessions, or competitions are much more eager to start a business and have a stronger entrepreneurial drive compared to those who have not. These results give more evidence to support our hypothesis. They also build on the research done by Huang et al. (2021) and Hardini and Taufiq (2021). The study shows the ES effects EI in its own unique and important way.

This study makes it clear that people cannot build college students’ desire to start a business all by itself. Instead, you need to actively develop important entrepreneurial qualities like being proactive, coming up with new ideas, and being willing to take risks. This has big consequences for schools and universities. Educational institutions should focus on offering a complete, multi-faceted kind of entrepreneurship education. This education should zero in on developing those specific traits, rather than just teaching general business stuff. Also, the fact that there is a close link between taking part in entrepreneurship-related activities and having a stronger entrepreneurial attitude tells us something important. It shows that practical experiences, like joining competitions, going to hands-on workshops, or being part of incubator programs, are super important. These experiences are key for helping students develop a strong entrepreneurial way of thinking.

Schools and universities should think about tailoring entrepreneurship education to different academic disciplines. They need to recognize that students from various majors might need customized help and growth plans to unlock their full entrepreneurial potential. In the end, these findings suggest that people need a more comprehensive and hands-on approach to teaching entrepreneurship. This approach should be inclusive, focus on specific skills, and blend theoretical knowledge with practical, real-world experiences.

5 Conclusion

With the lingering economic effects of COVID-19 in China, the landscape for college students looking to start their own businesses has gotten a lot tougher. In this difficult situation, boosting college students’ eagerness to start a business and their related skills has become a pressing matter for educators and policymakers. One good way to deal with this problem is to incorporate entrepreneurship education more thoroughly into the curriculums of higher education. To dig deeper into this approach, this study carried out a survey using questionnaires. The aim is to carefully study the entrepreneurial qualities of college students. It also aimed to figure out how the three main aspects of the ES-being proactive, being innovative, and being willing to take risks-affect their intention to start a business.

The results show that students’ different academic majors do not make a statistically significant difference when it comes to innovation. However, we can clearly see significant differences in their entrepreneurial eagerness, proactiveness, and willingness to take risks. This indicates that a student’s field of study affects some entrepreneurial qualities more than others. Moreover, the study validates that the ES has a major influence on EI. Among the elements of the ES, proactiveness and risk - taking have a more powerful impact compared to innovation. This backs up the initial idea that college students’ ES and their desire to start a business are positively linked. Through both regression and correlation analyses, it has been further demonstrated that the ES serves as a highly reliable and significant factor for predicting EI.

These results have multiple practical uses. First, colleges and universities need to go beyond just teaching theory in entrepreneurship education. Instead, they should focus more on shaping students’ behaviors. This can be done by using hands—on learning, mentorship, and giving students real-life experiences in entrepreneurship to help them become more proactive and better at handling risks. Second, because some majors do not naturally encourage entrepreneurial qualities as much, schools should think about using interdisciplinary education models. This way, students from every field will have the same chance to learn entrepreneurial thinking.

These results acquire significance when analyzed through theoretical frameworks like Social Cognitive Theory, which emphasizes mastery experiences, environmental stimuli, and self-efficacy in entrepreneurial behavior. Students studying management, law, or medicine benefit from learning environments that help them make decisions, deal with uncertainty, and spot opportunities, which boosts their confidence in their ability to start a business. Cognitive-behavioral theory posits that risk-taking and proactivity are significant predictors of emotional intelligence, as they entail engagement with complex tasks that foster resilience and adaptive coping mechanisms. Cognitive psychology elucidates that innovation arises from individual cognitive predispositions rather than solely from academic training, facilitating a significant transition from descriptive findings to thorough explanations.

These findings synthesize conceptual, theoretical, and practical contributions. They highlight that entrepreneurial intention requires interaction among cognitive capacity, behavioral disposition, and environmental reinforcement. Education should focus on discipline-sensitive, experience-driven, and behavior-focused approaches. This study confirms innovation as a cognitive trait, extends proactiveness and risk-taking as primary behavioral drivers, and challenges prior assumptions about discipline-specific innovation.

Finally, the study recognizes its own shortcomings, especially when it comes to the size of the sample and its overall scope. Due to these limitations, future research efforts should aim to increase the geographical and demographic range of the survey. By doing so, it will be possible to enhance which the study’s findings can be applied to different situations. Both government departments and educational institutions are urged to back more comprehensive, country-wide studies. It can be used to inform the creation of policies and curricula that are based on solid evidence.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

HR: Investigation, Methodology, Data curation, Resources, Conceptualization, Funding acquisition, Formal analysis, Writing – original draft. MZ: Resources, Project administration, Writing – review & editing, Supervision, Software, Methodology. CM: Writing – review & editing, Formal analysis, Visualization, Data curation, Validation, Conceptualization, Methodology.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research has been supported by the Doctoral Fund of Chongqing Industry Polytechnic College (NO. 2023GZYBSSK1-01) and is awarded to HR.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

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