Impact of collaborative,entrepreneurship education on the financial risk taken by university students

Abstract

Based on the definition of entrepreneurship, entrepreneurs can be considered as risk-takers. The literature contains conflicting theories as to whether risk-taking can be influenced by external factors. The current paper investigates the effect of entrepreneurship education and collaborative environment on financial risk-taking behavior among university-age young people. To this end, an online survey was conducted involving 510 participants and various statistical tests were utilized to test the research hypothesis. To measure financial risk-taking propensity, the Choice Dilemma Questionnaire methodology was implemented. The results of the analysis reveal that both the level of entrepreneurship education and a collaborative environment increase financial risk-taking. Moreover, multiple linear regression methodology was used to capture the significant factors that influence financial risk-taking when investing alone and investing in a collaborative environment. As a policy recommendation, the authors suggest that an entrepreneurship training curriculum should be developed that incorporates the various activities and elements of a collaborative environment.

Keywords

Higher education entrepreneurship education collaborative environment risk-taking behavior

An entrepreneur is a person who seeks opportunities and attempts to realize entrepreneurial activities by taking necessary risks when they identify such opportunities. In the last decade, entrepreneurship has attracted increasing attention from researchers and decision makers due to its key role in providing solutions to issues like unemployment and economic stagnation. It seems indisputable that entrepreneurship, in its various forms, is an essential part of any economy and that most economic processes are related to the activities of entrepreneurs. One of the most important paths to entrepreneurship is education (Hasan et al., 2017), and there is a growing emphasis on entrepreneurship education in higher education institutions (HEIs) (Castro et al., 2017), since university students are potential entrepreneurs of the future. The purpose of entrepreneurship education programs is to provide individuals with basic entrepreneurial skills and technical knowledge to establish and manage their own businesses. Regardless of whether or not the individuals who receive this training become entrepreneurs, they may contribute to the development of an entrepreneurship culture (Özdemir et al., 2016).

Notably, the intention to become an entrepreneur is closely related to risk-taking propensity (Embi et al., 2019). However, studies on the theoretical link between entrepreneurship education and financial risk-taking appear to adopt conflicting approaches, with some considering risk-taking propensity a personality trait (Zuckerman, 1991) and others seeing it as a cognitive behavior (Kahneman et al., 1982). Moreover, though education is believed to increase students’ risk-taking propensity, some studies do not support this claim. In fact, entrepreneurship education has increased substantially over the years, yet students remain risk-averse. This inverse pattern of non-parallel growth is noticeable in extant research evidence. Thus, we are driven to question the validity of the assumption of a direct relationship between education and risk-taking. Our first objective is to empirically examine the effect of entrepreneurship education on financial risk-taking. Aside from entrepreneurship education, we believe that low financial risk-taking may be affected by the lack of a collaborative environment (since such an environment enhances the ability of students to take risks in collaboration with peers rather than bear risks alone). Accordingly, our second objective is to determine the degree to which a collaborative environment impacts financial risk-taking.

This paper is significant in several ways. First, it adds to the growing yet inconclusive literature on the relationships among education, risk-taking, and entrepreneurship. Second, we contribute to the knowledge on entrepreneurship education by investigating the direct channels linking entrepreneurial risk-taking to a collaborative environment.

There are four remaining sections of this paper. The following section reviews the relevant literature. The subsequent section discusses the methodology, specifically the description of data and the construction of the experimental model. The penultimate section presents and elaborates on our results, and in the final section we offer our concluding remarks.

Literature review

In recent years, studies linking education to entrepreneurship have captured the attention of researchers and policy makers because of the potential effects of entrepreneurship on the economy. Entrepreneurs are prone to be productive, inventive, dynamic, and risk-tolerant (Stevenson and Gumpert, 1985). Entrepreneurial risk-taking propensity reflects one’s inclination to undertake risks (Antoncic et al., 2018; Sitkin and Weingart, 1995). Dating back to Cantillon (1734), risk-taking propensity has been widely considered to be a major characteristic of the entrepreneur (Block et al., 2015; Hisrich and Peters, 1998; Knight, 1921; McClelland, 1961; Schumpeter, 1934), despite some contradictory perspectives (e.g., Brockhaus, 1980; Miner and Raju, 2004). In fact, when establishing new business start-ups, entrepreneurs often face financial, psychological, and social risks (Hisrich and Peters, 1998; Nicholson et al., 2005). Stewart and Roth’s (2001) meta-analysis showed that compared to managers, entrepreneurs tend to have a greater proclivity to take risks. However, this does not mean they have an extreme risk-taking propensity (De Vries, 1977); rather, entrepreneurs usually engage in moderate risk-taking (Antoncic et al., 2015). There are essentially three different theoretical frameworks on risk-taking (Byrnes et al., 1999). For some researchers, risk-taking is considered a personality trait (Zuckerman, 1991); for others, it is a cognitive behavior (Kahneman et al., 1982). Then, there are those who believe these two perspectives to be complementary explanations (Antoncic et al., 2018). In this paper, we adopt the second theoretical framework, which regards risk-taking as a cognitive behavior (Palich and Bagby, 1995). The psychological perspective of the theory of planned behavior (TPB) (Ajzen, 1991) explains the cognitive process through which beliefs and attitudes transform into behavior. In particular, the intention to take a risk has a positive correlation with actual risk-taking behavior (Antoncic, 2003). Thus, the cognitive inclinations of entrepreneurs form their distinctive behaviors (Shaver and Scott, 1992), and this has important implications for entrepreneurship education. However, existing evidence generally offers opposing views on the effect of entrepreneurship education on risk-taking propensity.

One strand of the literature is of the view that entrepreneurship education might not result in improved entrepreneurial skills. Henry et al. (2005) indicated that while certain entrepreneurial skills can be taught through traditional education approaches, entrepreneurial creativity and innovation require experiential pedagogy and practical education which university lecturers typically fail to deliver, thus preventing successful entrepreneurship. Consistent with this, Henry et al. (2005) review of theory-based curricula revealed that entrepreneurship education does not increase the number of start-ups. Likewise, Pittaway and Cope (2007a, 2007b) posited that extant empirical findings corroborate the notion that while entrepreneurship education improves a student’s propensity and intention to become an entrepreneur, it remains uncertain if and to what degree such intention is expressed as actual entrepreneurial behavior.

In contrast, a number of studies (Gorman et al., 1997; Solomon et al., 1994) advocate that successful entrepreneurship can be achieved via education. Specifically, using a panel model of 99 countries, Solomon et al. (1994) found empirical evidence that the values, knowledge, and skills necessary for successful entrepreneurship can be accumulated via education. Their findings were confirmed by Garavan and O’Cinneide (1994a) and Gorman et al. (1997) Reasons for the positive impact of entrepreneurship education include (i) practical experiments, which may translate into resilience (Henry et al., 2005; Pittaway and Cope, 2007a, 2007b) (ii) less fear of risk and failure, which encourages students to try entrepreneurship; and (iii) the transmission of knowledge as well as the promotion of experience, which eventually leads to successful entrepreneurship. Another recent study (Arpiainen and Kurczewska, 2017) shows the importance of project-based entrepreneurship education and team learning on risk-taking and coping with uncertainty.

Various constructs have been developed to evaluate risk-taking propensity, anchored in theories like the Everyday Risk Inventory Scale (Steketee and Frost, 1994), the Sensation Seeking Scale (Zuckerman, 2009), the Tension Risk Adventure Inventory (Keinan et al., 1984), and the Risk Propensity Scale (Meertens and Lion, 2008). We note that while some researchers propose risk-taking propensity as a multidimensional construct (Caird, 1989; Kogan and Wallach, 1964), it is mostly considered to be unidimensional (Kamalanabhan et al., 2006). The most commonly used scales are based on the idea that a person with high risk-taking propensity would tend to choose an option with a smaller probability of success but higher utility, as evidenced by the Choice Dilemma Questionnaire (Kogan and Wallach, 1964) and the five choices of Schneider and Lopes (1986). In these questionnaires, participants are given choices of gaining less money with certainty against gaining more money with reduced probabilities. On the other hand, Kamalanabhan et al. (2006) developed a Magnitude of Loss Questionnaire based on the opposing idea that risk-taking is related to the size of the loss involved in a venture.

In view of the above literature, we address two research questions in this paper:

(a) Does entrepreneurship education affect risk-taking propensity?

(b) Does a collaborative environment enhance risk-taking propensity?

Methodology

Data

Data were obtained via a survey questionnaire that was administered to 510 participants (60.2% female and 39.8% male). The participants were mainly undergraduate students (48.6% freshmen, 18.2% sophomores, 10.8% juniors, 18% seniors, and 4.3% graduated) in universities in Kazakhstan across various majors (45.1% Education, 35.3% Engineering and Computer Science, 10.8% Economics, 5.9% Jurisprudence, and 2.9% Other) for which the medium of instruction was English. Using the snowball sampling technique, the data collection process took about 6 months. Aside from demographic questions, the survey contained three multiple choice questions (MCQs) to measure the level of entrepreneurship education, two MCQs to measure financial risk-taking, and one MCQ to measure financial risk-taking in a collaborative environment.

Our dependent variable was financial risk-taking. Our approach to measuring financial risk-taking was similar to the methodology followed in the Choice Dilemma Questionnaire (Kogan and Wallach, 1964): We aimed to capture an individual’s financial risk capacity and risk appetite when the expected outcomes were the same. To this end, our questionnaire contained two experimental questions, RISK1 and RISK2. In RISK1, two choices were given to the respondent:

(A). Guaranteed $100 win.

(B). Flip a coin; heads means you win $200 and tails means you win $0.

As shown in Table 1, we see that the expected outcome in either case is the same, namely, a $100 gain. The difference is that in the latter choice, the risk is higher.

Table 1.

The payoffs and corresponding risk classifications for the RISK1 variable.

	Event, %	Payoff
A	100	100
B	50	200

On the other hand, in RISK2, we asked respondents to select one of four investment options:

(A). 100% chance of gaining a $10,000 profit.

(B). 50% chance of gaining a $20,000 profit and 50% chance of going bankrupt.

(C). 25% chance of gaining a $40,000 profit and 75% chance of going bankrupt.

(D). 10% chance of gaining a $100,000 profit and 90% chance of going bankrupt.

As in RISK1, all four options have the same expected outcome (i.e., $10,000), with the only difference being the level of risk-taking (see Table 2). As opposed to RISK1, the expected outcome here is much higher.

Table 2.

The payoffs and corresponding risk classifications for the RISK2 variable.

	Event, %	Payoff
A	100	10,000
B	50	20,000
C	25	40,000
D	10	100,000

Education was one of our primary independent variables of interest. In this research, the three items used to measure education were adapted from Barro and Lee (1996); these were the number of hours spent training in entrepreneurship (EDU1), the number of books read on entrepreneurship (EDU2), and the successful completion of an entrepreneurship course (EDU3).

Finally, to measure financial risk-taking in a collaborative environment, we posed a question (RISK2C) asking how the participants would respond to investment options in a collaborative environment, with the four choices listed in RISK2. All these questions were regarded as categorical variables.

Method of estimation

This section specifies the methodology employed in this study to investigate the linkages between financial risk-taking, education, and a collaborative environment. To investigate these relationships separately and to compare individuals’ risk-taking independently with their risk-taking in a collaborative group setting, we utilized experimental and multinomial logistic regression. In addition, the ANOVA test was adopted as our main empirical technique to examine the concurrent relationships among the variables. The hierarchical approach was subsequently used to verify the moderation effect on the entire sample (Baron and Kenny, 1986). The model estimate was

R I S K 2_{i} = δ_{0} + δ_{2} \cdot ED U_{i} + δ_{3}^{j} \cdot X_{i}^{j} + ε_{i}

(1)

where

R I S K 2_{i}

is the measure of risk-taking,

ED U_{i}

is the vector variable capturing education,

X_{i t}^{j}

is the vector of the control variables that may influence risk-taking (i.e., gender, location, parent’s occupation, major, and years of study), and

ε_{t}

is the error term.

Results

In this section, we report and interpret our findings from the statistical analysis to answer our research questions.

Education and financial risk-taking

First, we seek to explain the possible effect of entrepreneurship education on financial risk-taking propensity. As explained above, three items were used to measure entrepreneurship education while two experimental questions estimated financial risk-taking propensity. Table 3 shows the correlations between these five items. Since our data were cross-sectional in nature, they may have captured correlational results that do not necessarily imply causality. Except for one pair (RISK1 and EDU1), all the correlations showed significantly positive associations (

p < 0.05

). This provides evidence that entrepreneurship education encourages financial risk-taking.

Table 3.

Correlation between risk-taking and different measures of education.

	EDU1	EDU2	EDU3	RISK1	RISK2
EDU1	1
EDU2	0.463**	1
EDU3	0.370**	0.338**	1
RISK1	0.075	0.134**	0.098*	1
RISK2	0.158**	0.154**	0.179**	0.260**	1

Note: ** p < .01; * p < .05.

Since all the variables were categorical, we extended our analysis to include a statistical t-test and an analysis of variance. First, as EDU3 was dichotomous, we conducted an independent sample t-test to compare the means, the results of which are reflected in Table 4.

Table 4.

Independent sample t-test on RISK1 and RISK2 with EDU3 as a group variable.

	EDU3 = 0			EDU3 = 1
	N	Mean	SD	N	Mean	SD	Mean (St. error) of difference	95% CI Lower	95% CI Upper	t	df	p-value
RISK1	393	0.34	0.475	117	0.45	0.5	−0.112 (0.051)	−0.211	−0.013	−2.214	508	.027
RISK2	393	0.70	0.782	117	1.04	0.781	−0.338 (0.082)	−0.5	−0.176	−4.104	508	.000

It was revealed that individuals who had passed an entrepreneurship course showed higher financial risk-taking propensity than those who had not [

t (508) = - 2.214, p = 0.027

for RISK1 and

t (508) = - 4.104, p < 0.001

for RISK2]. So, we conclude that individuals who pass at least one undergraduate course on entrepreneurship would likely have a higher financial risk-taking propensity. Next, the frequency distribution of choices for RISK2, grouped according to EDU3, and the results of the analysis of variance are presented in Table 5.

Table 5.

Financial risk-taking (RISK2) differences among respondents based on whether or not they passed an entrepreneurship course.


	EDU3 = 0	EDU3 = 1	F	p
A	182	26	5.1	.00
B	158	67	8.5	.00
C	40	17	4.7	.00
D	13	7	6.2	.00

We now turn to the analysis of variance for financial risk-taking according to the hours of training on entrepreneurship received; that is, the variable EDU1. The means of the risk items for EDU1 group and their 95% confidence intervals (CI) are given in Figure 1. As shown in the figure, there are increasing trends in both RISK1 and RISK2 with a higher number of training hours.

Figure 1.

Error bars represent the mean and 95% CI for risk variables based on EDU1.

To justify whether the increasing trend in RISK2 is statistically significant, the results of the ANOVA test are presented in Table 6. Indeed, in all choices, the differences exhibited statistical significance (4.2 < F, p < 0.001). Thus, we again conclude that education increases financial risk-taking. These results were also confirmed by the statistical analysis of financial risk-taking with the third variable, EDU2, as shown in Table 7 and Figure 2.

Table 6.

Financial risk-taking differences according to respondents’ hours of entrepreneurship training.


	EDU1 < 10	10 < EDU1 < 20	20 < EDU1 < 30	30 < EDU1	F	p
A	156	32	11	9	6.1	.00
B	126	66	14	19	7.1	.00
C	34	5	12	6	4.2	.00
D	12	3	4	1	5.3	.00

Table 7.

Financial risk-taking differences depending on the number of books on entrepreneurship read by respondents.

	EDU2 < 1	1 < EDU2 < 3	4 < EDU2 <6	7 < EDU2	F	p
A	106	76	19	7	7.1	.00
B	86	97	31	11	4.7	.00
C	15	30	10	2	6.8	.00
D	6	9	3	2	5.4	.00

Figure 2.

Error bars represent the mean and 95% CI for risk variables based on EDU2.

Collaborative environment and financial risk-taking

To answer our second research question, on whether a collaborative environment (students to take risks in collaboration with peers rather than alone) increases risk-taking propensity, we performed a paired sample t-test on RISK2 and RISK2C (see Table 8). The results confirm that there is a greater likelihood of individuals adopting risk in a collaborative environment (

M = 0.92, S D = 0.847

) than when they are investing alone (

M = 0.78, S D = 0.794

); this result was statistically significant (

t (509) = - 3.319, p = 0.001

Table 8.

Paired sample t-test on RISK2 and RISK2C.

	RISK2		RISK2C
N	Mean	SD	Mean	SD	Mean (St Error) of difference	95% CI Lower	95% CI Upper	t	df	p-value
510	0.78	0.794	0.92	0.847	−0.133 (0.907)	−0.212	−0.054	−3.319	509	.001

The frequency comparison of respondents’ answers to the choices in RISK2 and RISK2C are presented in Figure 3. It is evident that when investing alone, individuals are more likely to avoid risk (41%) than when they are in a collaborative environment (35%). Moreover, all choices related to levels of risk-taking (B–D) appeared to be higher for individuals investing in a collaborative environment. As shown in Table 9, these differences were statistically significant.

Figure 3.

Comparison of the distribution of answers to choices for RISK2 and RISK2C.

Table 9.

Financial risk-taking differences between RISK2 and RISK2C.

	RISK2 Mean	RISK2C Mean	t-test	p
A	208	176	7.1	.00
B	225	231	4.7	.00
C	57	73	6.8	.00
D	20	30	5.4	.00

Finally, we performed a separate multiple linear regression analysis for both RISK2 and RISK2C to analyze the predictor variables in each situation, the results of which are shown in Table 10. We see that when investing alone, the predictor variables EDU1, EDU3, D.Male, D.Village, and the constant term were statistically significant in predicting RISK2. As for investment in a collaborative environment, aside from the constant term, only EDU2 was a statistically significant predictor of RISK2.

Table 10.

Differences in regression results for RISK2 and RISK2C.

Variables	Alone (1)	Collaborative (2)
EDU1	0.0763* (0.0456)	−0.0584 (0.0495)
EDU2	0.0659 (0.0487)	0.159*** (0.0530)
EDU3	0.245*** (0.0916)	−0.0190 (0.0997)
D.Male	−0.136* (0.0763)	−0.0839 (0.0830)
D.Education	−0.0767 (0.120)	−0.163 (0.131)
D.Engineering	0.00649 (0.126)	−0.0384 (0.137)
D.Law	−0.0727 (0.165)	−0.156 (0.179)
D.Village	0.174** (0.0783)	0.0656 (0.0851)
D.Parents occupation	0.0220 (0.0727)	−0.0288 (0.0790)
Constant	0.525*** (0.145)	0.853*** (0.157)
Observations	510	510
R-squared	0.062	0.026

Note: * p < .05; ** p < .01; *** p < .001.

Discussion

In this paper, we study two potential factors affecting the financial risk-taking propensity of individuals. More specifically, we were interested to find out whether entrepreneurship education and a collaborative environment affect financial risk-taking propensity. The findings show that both education and a collaborative environment do indeed increase financial risk-taking. This section interprets and discusses these findings in more detail.

According to Palich and Bagby (1995), entrepreneurial risk-taking can be considered a cognitive behavior. Entrepreneurs are more likely to choose risky options when starting up a venture as they approach a given situation with “unwarranted optimism” (Baron, 2004). This perspective hints that financial risk-taking can be altered with entrepreneurship education. Indeed, our findings suggest that entrepreneurship education increases financial risk-taking propensity. This is evidenced by all three entrepreneurship education-related factors (i.e., hours of training, number of books read, and passing of an entrepreneurship course) showing significant effects (p < .01) in all the statistical tests conducted. While these three variables are correlated with each other (see Table 3), the degree of correlation is not strong. So, we may assume that they measure somewhat different aspects of entrepreneurship education. From Table 3, we can also see that all three variables have roughly the same positive correlation with RISK2, with Pearson’s correlation coefficient (r) ranging from 0.154 to 0.179. While possessing statistical significance (p < .05), the degree of association is weak.

The second chart in Figure 1 implies that individuals who receive less than 20 hours of entrepreneurial training have, on average, lower financial risk-taking propensity than those with more than 20 hours of training. Surprisingly, individuals with over 30 hours of training also exhibit lower risk-taking propensity than those with 20–30 hours of training, indicating an optimal duration of training to enhance risk-taking. It might be due to chance as the two 95% confidence intervals overlap. In any case, this unexpected observation should be further investigated in future work. In Figure 2, we see that individuals who have not read any books on entrepreneurship would take fewer financial risks than those who have read at least one book on entrepreneurship. On the other hand, there seems to be no significant difference in risk-taking when an individual reads any number of books beyond one. The independent sample t-test result further shows that individuals who pass at least one undergraduate entrepreneurship course are more likely to select option B (win with 50% risk), while individuals who have not passed any such course tend to choose the less risky option A (guaranteed win).

The findings regarding our second research question suggest that a collaborative environment is useful for financial risk-taking propensity. The paired sample t-test (Table 8) was significant; hence, we can safely reject the null hypothesis that a collaborative environment has no effect on financial risk-taking. Individuals who invest alone are more likely to avoid risky options as opposed to those investing in a collaborative setting with others. We also conducted multiple regression analysis to compare the predictor variables for individual versus group financial risk-taking propensity. For individuals investing alone, the number of training hours and passing a course on entrepreneurship play crucial roles as educational factors that increase risk-taking intention. However, for individuals investing in a collaborative environment, the number of books read is the only significant predictor of risk-taking. Gender emerged as another statistically significant predictor of financial risk-taking when investing alone. That is, females appear to be more likely to choose less risky options when investing alone. In contrast, gender does not matter in a collaborative environment. Finally, the place where an individual grows up appears to be another predictor of risk-taking when investing alone. In particular, individuals who grow up in a rural area are more likely to select riskier options when investing on their own than those raised in an urban area.

Conclusion

The main objectives of this study were to investigate the impacts of entrepreneurship education and a collaborative environment on financial risk-taking propensity. To fulfill these objectives, we acquired cross-sectional data from 510 university students and subjected it to various statistical tests, including a t-test, ANOVA, and multiple regression analysis. The results confirmed the positive effects of education and a collaborative environment on financial risk-taking. Since our data were cross-sectional in nature, they may have captured correlational results that do not necessarily imply causality. One possible direction for future research would be to carry out a longitudinal study to make causal inferences linking financial risk-taking, education, and a collaborative environment. As education and a collaborative environment both increase financial risk-taking propensity, it would be pertinent to develop an entrepreneurship training curriculum that incorporates the various activities and elements of a collaborative environment.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Shirali Kadyrov

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