Effect Of Risk Taking Propensity On Entrepreneurial Intentions Among Students Undertaking Entrepreneurial Course In Universities In Meru And Tharaka Nithi Counties.

Effect of Risk-Taking Propensity on Entrepreneurial Intentions among Students Undertaking Entrepreneurial Course in Universities in Meru and Tharaka Nithi Counties

Kelvin Kimathi Gikunda, Professor Gilbert Mugambi Miriti

Faculty of Business Studies, Chuka

DOI: https://dx.doi.org/10.47772/IJRISS.2025.9010023

Received: 17 December 2024; Accepted: 24 December 2024; Published: 28 January 2025

ABSTRACT

The concept of entrepreneurship has received increasing attention in various countries globally, especially in developing countries which suffer from several problems that hinder economic growth. Entrepreneurship is essential in addressing economic problems, such as unemployment, new wealth creation, stabilizing society, increasing industrial competition and economic development. The main objective of this study was to determine the effect of risk taking propensity on entrepreneurial intentions among students in universities in Meru and Tharaka Nithi counties. This study was conducted among university students since the students had undertaken entrepreneurial training to become future entrepreneurs. Descriptive research was adopted. The target population of this study was 800 students and a sample size of 267 respondents who were in third and fourth years and had undertaken entrepreneurial studies as a unit or major course at the universities. This study was anchored on theory of planned behavior and entrepreneurship event model of entrepreneurship. A questionnaire was used to guide in collecting primary data. Data obtained from this study was interpreted using descriptive statistical methods including tables, mean, median, mode and simple percentiles. Data was analyzed using inferential statistics with help of SPSS. Multiple regression analysis was used to analyze the relationship between variables using confidence level of 95%. The study found a regression coefficient of risk taking propensity was 0.187 and a p-value of 0.000<0.05 hence risk taking propensity had a positive and statistically significant effect on entrepreneurial intentions. It is recommended that Universities should encourage and create an environment that fosters calculated risk taking and confidence among the students to believe in their abilities, identify and take up opportunities available

Keywords: Entrepreneurial orientation, risk taking, entrepreneurial intentions, entrepreneurial mindset, creativity and innovation.

INTRODUCTION

Risk-taking tendencies include managing hazards and being willing to accept them. An individual with entrepreneurial aspirations is most risk-oriented (Karabulut, 2016). According to Haruna (2018) a person’s tendency for taking risks reveals how they handle situations involving risky decisions. To think and act entrepreneurially, one must be willing to take risks (Farruk, 2017). Risk-taking is a trait that reveals a person’s propensity and willingness to take risks (Fayolle & Linan, 2014). Entrepreneurial behavior is associated with a moderate level of personal risk (Hansen ,2021). Kisolo (2016) asserts that business owners are more likely than managers to take risks. Risk-taking is more common among entrepreneurs than it is among non-entrepreneurs and they also think differently about the likelihood that a new company would thrive (Haruna, 2018).

According to Kisolo (2016) business owners tend to take moderate risks. Bachikirov and Kakkonen (2018) states that an entrepreneur faces personal risks, social risks and psychological risks. High levels of ingenuity drive people to work for themselves (Hansen, 2021). For this to take place requires some level of risk taking. In a study conducted by Bachkirov and Kakkonen (2018), 1414 students from six different European nations were researched to assess the significance of risk-taking tendency about entrepreneurship tendencies. As a result, it was discovered that preference for taking risks was positively connected with the rise of entrepreneurship intents. However, this research was done in a European context thus it might not be appropriate in an African context.

Entrepreneurship is a strategy for producing something fresh and distinctive from what already exists in order to improve human wellbeing and advance society (Chhabra et.al., 2020). According to Farruk (2018) an entrepreneur is somebody who has the capacity to employ resources like capital, land, labor and raw materials to develop a new service, method or enterprise. Entrepreneurship means being a business owner, however not all entrepreneurs are business owners (Bwisa, 2019). According to (Rauch & Freese,2009) Entrepreneurship is the process of creating unique, added-value products and taking calculated risks in exchange for a rewarding material and emotional gain. A person with entrepreneurial intentions is one who intends to launch a business in less than three years (Whegher et al., 2019).

An intellectual or mental state known as the entrepreneurial intention motivates people to concentrate on a specific objective (Chhabra et al., 2020). Understanding the role that intention plays in the business journey is crucial, Verheul et al., (2019) assert that comprehension Understanding the underlying motivations for the entrepreneurial process requires an understanding of entrepreneurial intention. Investigations into numerous research have also shown that the intentions play a role in how well a commercial enterprise is formed. (Wegner et al. (2019).

Bird (1988) asserts that having an entrepreneurial intention is having a mental condition that energizes and points one to start and operate a new firm. Entrepreneurial intention according to Van Moriano et al. (2008), is the ambition to launch a commercial enterprise in the future. Entrepreneurship intention is the main indicator of prospective entrepreneurs according to earlier study (Krueger et al., 2000). He goes on to state that analyzing intention as opposed to personality traits or environmental circumstances can better predict entrepreneurial activity. Ajzen (1991) asserts that perceptions of behavioral control, attitudes toward an activity and subjective norms can all be utilized to accurately forecast a person’s intentions to carry out a variety of acts.

One’s attitude and deeds are significantly influenced by their intentions (Nguyen, 2020).  According to Majid and Yusuf’s (2020), the individual intentions aid in creating one’s final objective as well as the necessary actions to accomplish these aims. According to research on the relationship between gender and entrepreneurial intentions, men are more likely than women to have such intentions. According to some experts the reason why women have lower entrepreneurial inclinations may be related to obligations related to the home and family (Farukh & Waheed, 2019).

Kenya has put efforts in improving education system, as reflected in the national budget 2019, 25% of national budget was allocated to higher education (KNBS, 2020) to change education sector in both context and structure. The 2-6-6-3 system, which includes the primary, secondary, and higher education systems today, is competency-based. The government started to acknowledge the value of higher education in 1985. They included middle level colleges as well as public and private universities (Bwisa, 2019). These served as Kenya’s economy’s pillars of growth. In Kenya, entrepreneurship is viewed as a means of absorbing and reducing the rising unemployment rate among university graduates. According to the Commission of University Education (CUE), there are 4 universities in Meru and Tharaka Nithi counties and all of them offer entrepreneurship courses  in their schools, faculties or departments (Njoroge, 2019) All of this is consistent with vision 2030, which aims to develop a human resource that is competitive globally and adaptable to meet the needs of the first industrializing economy (Bwisa, 2019).

Whether or not students choose to engage in entrepreneurial undertakings depends on a variety of circumstances.  According to Verheaul (2019)   women are less likely than males to want to launch their own firm. He goes on to say that women are constantly averse to taking chances. One of the determinants discovered was the parents’ occupation (Verheaul, 2019). There are different types of students and depending on their personality, some are more inclined to start their own businesses than other people (Ghazali & Bon, 2019).

Kenya formal employment is fewer compared to the number of graduating students looking for job opportunities (Bwisa, 2019). With this in mind, majority of  student ts fear to start businesses that may later collapse and render them jobless. Hence prefer the comfort of monthly income from employment (Ghazali & Bon, 2019).

Theoretical Review

A theoretical review is a thorough and methodical examination of the theory to determine what concepts, constructions, and phenomena are there, their relationships, and the degree to which the theory has been tested in order to generate new theories (Njoroge, 2019).

Entrepreneurial Event Model

The entrepreneurial event model combines perceived attractiveness, perceived practicability and likelihood to predict entrepreneurial intention because it has been demonstrated that they correlate with one another (Krueger, 1993).

METHODOLOGY

This research was undertaken in universities in   Meru and Tharaka Nithi Counties. Meru and Tharaka Nithi Counties have four universities namely Chuka University, Meru University of Science and Technology, Kenya Methodist University and Tharaka university. The study focused on third and fourth year students who had undertaken entrepreneurial courses at degree level. Universities in Meru and Tharaka Nithi offer entrepreneurship training to their students to face entrepreneurial world. Meru and Tharaka Nithi counties are located in eastern region of Kenya. The study adopted descriptive research design since it facilitated in choosing and grouping of the components and features of object.The researcher used a questionnaire to gather primary data. Primary data is significant since it entails generating new data from sources that already exist Descriptive and Inferential statistics were used to analyze data. Simple and Multiple linear regression analyses were then conducted using SPSS software version 25.0 in order to address study objective. Assumption of linear regression model of normality, multi-collinearity and heteroskedasticity were tested before analyzing data.

Sample Size Determination

A sample size was taken from all students in the three faculties who had undertaken entrepreneurship study as a unit or major courses in the four universities. To be carefully chosen in the sample the students’ need to have undertaken entrepreneurship training as a course. This would ensure the students selected have entrepreneurship knowledge and entrepreneurial skills. Using the Yamane formula (Yamane, 1967), Size of the study’s sample was determined in the following way:

\( n = \frac{N}{[1 + N e^2]} \)

Where,

n = Size of the sample

N = Size of the population

e = Precision level

The sample consisted of 267 students. The sample size allows a 5% error rate and a 95% range of confidence, making it statistically significant.

The study targeted to collect data using 267 questionnaires. Out of which it collected 220, translating to 82% return rate. This rate was excellent as it was more than 70 percent as presented in Figure 2 (Cooper and Schindler, 2019). Generally, there was a response rate of above 81% from the universities targeted.

Normality Test

To assess if the error term was normal, the researcher concentrated on the normality test. The use of the Kolmogorov-Smirnov test was made to assess for normalcy. Results presented in Table 1.

Table 1: Normality Test for the residual

Source: Survey Data, (2024)

Table 1 exemplifies the findings of the normalcy test for the variables. To evaluate whether the elements in this investigation were normally distributed, the Kolmogorov-Smirnov test was performed. Results show significance value for the study variables were > 0.05, hence showing a normal distribution of the residual. For sample sizes of more than one hundred, Kolmogorov-Smirnov test is recommended. Test statistics of greater than 0.05 indicate a normal distribution of the residual (Thode, 2016). Since the residual was normal, it was appropriate to employ in subsequent analysis.

Heteroscedasticity Test Results

When the error term’s variance fluctuates, this is known as heteroscedasticity. (Fisz, 2018). Measurement error and unequal population distribution are two factors that can cause it to occur. This notion casts doubt on the linear model of conventional regression, which attributes the error term variance remaining constant. Furthermore, when some crucial variables are excluded from the model, heteroscedasticity can also occur. P-P plots, according to Fisz (2018), are the best for showing the distribution of residuals and can be used to check for heteroscedasticity. The outcomes are shown in figure 3. In order to rule out measurement errors, subpopulation differences, and other interaction effects, heteroscedasticity was used. The residual plots method was used to examine heteroscedasticity.

Figure 1: Heteroskedasticity Test

Source: Survey Data, (2024)

Figure 1 presents the Heteroscedasticity test for the multiple regression model between entrepreneurial intentions and risk taking propensity. The widening of the residuals as the predicted variables rise is a sign of heteroscedasticity. There is no indication of heteroscedasticity from the graph above because the breadth of the plots does not rise or decrease uniformly as the anticipated variable increases and because no particular pattern developed.

Multicollinearity Test

The research employed the variance inflation factor (VIF) to do a multi-collinearity test in order to look at the tolerance levels. When all of the independent and dependent variables have tolerance values more than 0.1, there is no multi-collinearity, while when the VIF is greater than 10 (VIF = 10), there is a multi-collinearity issue (Field, 2009).

Table 2: Multi-collinearity Coefficients

Multi-collinearity was disregarded because every variable had tolerance values exceeding 0.1 and inflation of variance factors lower than 10. The results showed that multi-collinearity of the variables was not significant and the model’s level of multi-collinearity could thus be allowed. These results show that there is no intercorrelation between the explanatory factors, supporting the validity of the research’s conclusions.

Correlation establishes the direction of any relationship between any two variables. Zero indicates no correlation, while a coefficient of -1 denotes a completely inverse link between the variables. A coefficient of +1, however, shows a flawlessly positive correlation between the variables being studied. The Pearson Product Moment Correlation coefficient (r) which has a 5% level of significance was utilized in the study to assess the existence and strength of any correlations between various variables.

Table 3: Spearman Rank Correlation between Study Variables

The findings in Table 3 demonstrate that risk taking propensity has an impact on entrepreneurial intentions because they had a p-value of 0.000<0.05. Therefore, risk taking propensity was thus a reliable indicator of entrepreneurial intentions.

Analysis of Regression Model of Risk-Taking Propensity

To determine the effect of risk taking propensity on entrepreneurial intentions among students undertaking entrepreneurial courses in public and private universities in Meru and Tharaka Nithi Counties. The coefficients of risk taking propensity and its respective p-values are presented in Table 4(a), (b) and (c).

HO₁: There is no statistically significant relationship between risk taking propensity and among students undertaking entrepreneurial courses in universities in Meru and Tharaka Nithi Counties.

Table 4(a): Summary of the Regression Model 1

Source: Primary Data (2024)

Table 4 (b): Anova for Risk Taking Propensity

Source: Primary Data (2024)

Table 4(c): Coefficients Estimates of Risk Taking Propensity and Entrepreneurial Intentions

Source: Primary Data (2024)

The R² was 0.064 as shown in Table 4(a) which implies that 6.4% of changes in entrepreneurial intentions are caused by risk taking propensity while 93.6% of the changes in other elements outside the scope of the study, such as innovation and a supportive environment, influence entrepreneurial intentions.

Results shown in Table 4 (b), F-value (14.869) and a p-value (0.000) demonstrates the statistical significance of the model chosen since (p = 0.000 < 0.05). According to the study’s findings, the likelihood of taking risks is a good indicator of one’s inclination to start a business.

From Table 4 (c), the regression coefficient of risk-taking propensity was 0.187 and a p-value of 0.000<0.05 hence risk taking propensity had a positive and statistically significant effect on entrepreneurial intentions. Therefore, the null hypothesis, which claimed that a risk-taking inclination has no statistically substantial effect on entrepreneurial intentions, was found to be false. This implies that a change in the risk taking propensity directly affect entrepreneurial intentions since setting a clear plan of launching a new product to fill a gap in the industry directly affect entrepreneurial intentions. This result concurs with Bachkirov et al. (2018) who found that risk-taking tendency affected entrepreneurial goals. Therefore, the regression model for effect of risk taking propensity on entrepreneurial intentions can be expressed as follows:

Y=1.720+0.187X₃

Chi-Square Test of the Risk Taking Propensity

Using the chi square, the association between risk taking propensity and entrepreneurial intentions was investigated. Chi-square analyses of the individual elements are represented in Table 5.

Table 5: Chi-Square Test between Risk Taking Propensity and Entrepreneurial Intentions

Table 5 display the findings of the chi-square test between the risk taking propensity and entrepreneurial intention with a p-value of 0.000 < 0.05 implying that risk taking  has a significant effect on entrepreneurial intentions.

Summary of the Finding

The third objective examined the relationship between students’ tendency for taking risks when enrolled in entrepreneurial courses and entrepreneurial intentions at universities in the counties of Meru and Tharaka Nithi. The outcomes of this objective showed that the majority of students had clear plans for introducing a new product to close a market gap, which directly impacted on their entrepreneurial intentions. Further research found that risk-taking tendency influenced entrepreneurial courses favorably in colleges in the counties of Meru and Tharaka Nithi; as a result, it is a crucial component to take into account to enhance entrepreneurial intentions.

CONCLUSION

Results concluded that an increase in risk taking propensity leads to an increase in entrepreneurial intentions. Therefore universities should encourage students to embrace risk taking propensity strategies to be prepared for the uncertainty of the environment and this can enhance their entrepreneurial intentions.

RECOMMENDATIONS

Policy makers should pay attention to social support and risk-taking propensity as important factors in stimulating and entrenching entrepreneurship among the undergraduates. Developing policies and programme that would furthering entrepreneurship spirit in students is also an important plausible option. The existing compulsory entrepreneurship courses strengthened with practical contents could thereby create opportunities for students to pitch business ideas and start up business ventures.

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