From the questionnaires distributed to the total respondents 210 of them were filled and returned with appropriate response However, 16 questionnaires were not collected due to the fact that the questionnaires were distributed to the respondents and not filled by themselves.
Demographic Characteristics Of The Respondents
Table 2
Demographic Characteristics of the Respondents
NO | Description | Respondents |
Frequency | Percentage |
1. | Gender | | |
| Male | 112 | 53.3 |
| Female | 98 | 46.7 |
| Total | 210 | 100 |
2. | Age | - | - |
| 18–21 | 85 | 40.5 |
| 22–25 | 112 | 53.3 |
| 26 and above | 13 | 6.2 |
| Total | 210 | 100 |
3. | Department | - | - |
| Accounting and finance | 62 | 29.5 |
| Cooperative’s accounting and audit | 3 | 1.5 |
| Cooperative’s business management | 7 | 3.4 |
| Economics | 35 | 16.7 |
| Management | 86 | 40.9 |
| Marketing management | 17 | 8 |
| Total | 210 | 100 |
4. | Taking any Entrepreneurship Course | - | - |
| Yes | 210 | 100 |
| No | 0 | 0 |
| Total | 210 | 100 |
5. | Business Background | - | - |
| Yes | 32 | 15.2 |
| No | 178 | 84.8 |
| Total | 210 | 100 |
6. | Future career choice of respondents | - | - |
| Employee | 112 | 53.3 |
| Self-employed | 88 | 41.9 |
| Successor/to help out a family business | 5 | 2.4 |
| No plan | 5 | 2.4 |
| Total | 210 | 100 |
Source: Own survey, 2021 |
Regarding the gender composition, according to the table above, the distribution is balanced with slight inclination to male (53.3%) and the rest (46.7%) are female, this shows that in this study the number of respondents from both genders have fairly participated evenly (Table 2).
When we see the age composition of the respondents’ most of the sampled respondents’ age group falls between the ages of 22 up to 25 which accounts for 53.3 % of the total number of sampled respondents, and the rest 18–21, and 26 and above are 40.5% and 6.2 % respectively, this shows that the higher number of respondents are from the age group of 18–25 this implies most participants are in the youth category (Table 2).
According to the table from the total sample of 210 respondents the majority of the respondents (40.9%) were in the department of management followed by department of accounting and finance (29.5%) and (1.5%) of them were in the department of Cooperatives accounting and audit, and the other (3.4%) in Department of Cooperatives management, (16.7%) is in Department of economics and the remaining (8%) are in Department of marketing management. This shows that adequate number of respondents have been taken from all the departments (Table 2).
According to the table (100 %) take entrepreneurship course and no one respond as didn’t take any entrepreneurship courses.
According to the table above, (15.2%) responded saying that their families engaged in entrepreneurship while the rest (84.8%) say their families not engaged in entrepreneurship.
Right after graduation (53.3%) of the student’s career choice is to be to be an employee in a company or organization, (41.9%) of the respondent choose a career as an entrepreneur / self-employed, (2.4%) of the students plan to be in the family business, and the remaining (2.4%) don’t have any plans (Table 2).
We can conclude that all departments in Wollo university faculty of business are included and almost all of them took an entrepreneurship course that means they are familiar and have known how about entrepreneurship in general.
Correlation Analysis
A Pearson Correlation Analysis was performed in SPSS to check if there is a linear relationship between the independent and dependent variables. Correlation analysis shows the degree of association and relation between variables and it indicates the direction in which the variables relate and associate positively or negatively (Saunders, Lewis, & Thornhill, 2009).
Table 3
Correlations |
| | INT | GN | SN | EE | AC | PT | FB |
1 | INT | 1. | | | | | | |
2 | GN | .384* | 1. | | | | | |
3 | SN | .741* | .534* | 1. | | | | |
4 | EE | .653* | .546* | .574* | 1. | | | |
5 | AC | .681* | .547* | .597* | .512* | 1. | | |
6 | PT | .694* | .587* | .454* | .482* | .485* | 1. | |
7 | FB | .548* | .529* | .518* | .534* | .478* | .543* | 1. |
| **. Correlation is significant at the 0.01 level (2-tailed). | | | |
Source: own survey, 2021 |
The values of correlation ranges from − 1 to 1, Correlation coefficient able to measure the strength and the association of the linear relationship between two variables (Cohen and Holliday, 1983).
As cited by Bryman and Cramer (1999) proposed the range of correlation coefficient as 0.19 and below = very low; 0.20 to 0.39 = low; 0.40 to 0.69 = modest; 0.70 to 0.89 = high, and 0.90 to 1 = very high.
In this study, in order to easily classify the strength and association between variables the researcher has been used correlation coefficient range of Cohen and Hollidays (1982).
As we can see from the above correlation table, the dependent variable; entrepreneurial intention has a strong and positive correlation with social norm (r = .741, P < 0.01) and access to capital (r = .724, P < 0.01). As we see the dependent variable entrepreneurial intention it also has a modest correlation with Gender (r = .384, P < 0.01), entrepreneurial education (r = 653, P < 0.01), personality trait (r = .694, P < 0.01), family background (r = .548, P < 0.01) these independent variables have a positive and significant relation with the dependent variable entrepreneurial intention. Also, most of the variables have modest relationship each other (Table 3).
Regression Analyses And Hypotheses Testing
Regression Analyses is a reliable method that allows to examine the relationship between two or more variables and to identify which variables have impact on the other variable. This study has one independent variable, six independent variables and the researcher use hierarchical regression analysis. Hierarchical regression analysis permits for a comparison between alternative models with and without interaction terms, where an interaction effect only exists if the interaction term contributes significantly to the variance explained in the dependent variable over the main effects of the independent variables (Jaccard &Turrisi, 2003).
Table 4
Model Summary |
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | Change Statistics |
R Square Change | F Change | Sig. |
1 | .762a | .581 | .562 | .39342 | .581 | .543 | .000 |
Source: own survey, SPSS, 2021 |
As shown the coefficient R in this model 1 summary indicates the square root of R and is the correlation between variables. From the table below, R = .762 indicates that there is a very strong positive correlation between the dependent variable and the other variables. R Square is a statistical measure that shows how close the data are to the fitted regression line. It is also known as the coefficient of determination or the coefficient of determination for regression, 0% indicates that the model explains none of the variability of the response data around its mean. The model 1 statistics of dependent variable entrepreneurial intention revealed that the R square value of .581. It means that all independent variables included in the model explained 58.1% of variance (.58x 100%). R square change is added when other predictors are added in dependent variable (Table 4).
Table 5
Coefficientsa |
Model | | Unstandardized Coefficients | Standardized Coefficients | t | Sig. |
B | Std. Error | Beta |
1 | (Constant) | − .850 | .379 | | -2.240 | .027 |
GN | .009 | .120 | .005 | .076 | .940 |
PT | .182 | .121 | .112 | 1.500 | .013 |
AC | .288 | .083 | .165 | 2.267 | .000 |
SN | .121 | .082 | .481 | 6.351 | .025 |
EE | .104 | .068 | .101 | 6.524 | .043 |
| FB | .134 | .081 | .116 | 7.542 | .036 |
Source own survey, SPSS 2021 |
H1: There is positive and significant relationship between demographic factors and entrepreneurial intention of university students.
This study assumed that there is positive and significant relationship between demographic factors and entrepreneurial intention. From several demographic factors this study tries to investigate the effect of Gender on the entrepreneurial intention of the university students. Based on the table above, gender was found to be statistically insignificance at a = .05 level (β = .009, p = .940), this shows that gender won’t affect entrepreneurial intention (Table 5).
H2. There is positive and significant relationship between personal factors and entrepreneurial intention of university students.
This study assumed that there is positive and significant relationship between personal factors (individual factors) and entrepreneurial intention. From several personal factors (individual factors) this study tries to investigate the impact of personality trait and access to capital on the entrepreneurial intention of the university students.
Based on the students reply, the results show that personality trait has a positive significant effect on entrepreneurial intention at a = .05 level, (β = .182 p = .013) this shows personality trait determines entrepreneurial intention. Therefore, there is a significant and positive relationship between personality traits and entrepreneurial intention (Table 5).
Based on the above coefficient table, access to capital was found to be positive and significance relationship at a = .05 level, (β = .288, p = .000) this shows access to capital has an effect on entrepreneurial intention (Table 5).
It can be observed in the table above, there is significant and positive relationship between both personality traits and access to capital which indicates that the proposed hypothesis ‘H2: There is positive and significant relationship between personal factors and entrepreneurial intention of university students’ is accepted.
H3: There is positive and significant relationship between Environmental factors and entrepreneurial intention.
Based on table above, social norm was found to be statistically significance at a = .05 level, (β = .121, p = .025), this shows in Wollo university student social norm determines entrepreneurial intention. And the other environmental factor is entrepreneurial education (Table 5).
Based on table above, entrepreneurial education was found to be statistically significance at a = .05 level, (β = .104, p = .043), this shows that entrepreneurial education determines entrepreneurial intention (Table 5).
The above result indicates that the proposed hypothesis’H3: There is positive and significant relationship between environmental factors and entrepreneurial intention of university students’ is accepted.
H4: There is positive and significant relationship between family background and entrepreneurial intention.
Based on the students reply, the results show that family background has a positive and significance effect at a = .05 level, (β = . 134, p = .036). This shows that e family background determines entrepreneurial intention (Table 5).
The above result indicates that the proposed ‘H4: There is positive and significant relationship between family background and entrepreneurial intention’ is accepted. Generally, in this research finding demographic factors does not determine entrepreneur intention while personal factors, environmental factors and family background determine entrepreneurial intention.