In this chapter, the data analysis result is presented in regards to the framework of the research. First, the descriptive analysis presents the demographic information of the samples.
Then, the mean, standard deviation, correlation between variables, and reliability of each variables are shown in the second section. Next, three stated Hypotheses are analyzed by using the hierarchical regression to test the influence of each independent variables on the dependent variable. Lastly, a comparison is proceeded by using t-test and One-way ANOVA on gender and career status groups in the level of entrepreneurial intention.
Descriptive Analysis
A preview of demographic profile of the sample for the valid data is presented through descriptive analysis and to confirm whether there are errors, outliers and the distribution among the valid data. The study collected 295 valid samples, and the career status among the data are full-time workers 73.9% (n = 218,), full time and part-time workers 10.8% (n = 32), part-time/
contractor/ seasonal/ temporary workers 6.1% (n = 18), and unemployed 9.2% (n = 27). The majority gender in this sample is female, 196 (66.4%) out of 295. There are 166 participants (56.3%) having a bachelor degree among the 295, and 104 with a master degree (35.3%), 18 graduated high school or below, and 7 a Ph.D. degree. The age of the data ranges from 20 to 54 years old. Age below 30 years old consisted 58.4% of the data, while 28.2% of participants were between 30-40 years old, and 13.6% above 40 years old.
Table 4.1.
Descriptive Statistics on Sample Demographics (N = 295)
Variable Category Frequency Percentage
Career Status
Pearson Correlation Analysis
The purpose of Pearson correlation analysis is to test the strength of hypothesized relationship of the study and to understand the relationship among the variables. In the correlation result, if the number is positive, it represents a positive relationship between the correlated variables; on the other hand, when the number is shown with a negative sign, the relationship between the correlated variables is negatively related. The correlation, mean, standard deviation, and reliability of each variables are presented in Table 4.2. As shown in Table 4.2, career adaptability (r = .15, p < 0.01), entrepreneurial opportunity (r = .61, p < 0.01), and risk aversion (r = -.12, p < 0.05) are significantly correlated with the dependent variable, entrepreneurial intention. However, risk aversion is negatively related to the dependent variable, while career adaptability and entrepreneurial opportunity are positively correlated with the dependent variable. Although career adaptability is correlated to entrepreneurial intention, the r value is not high, that is, career adaptability has a low correlation with the dependent variable. In the initial measurement of career adaptability, the variable was composed of four dimensions, which are concern, control, curiosity, and confidence, so the study also analyzed the relation among the variables with the four dimensions. However, only concern (r=.22, p<0.01) and curiosity (r=.15, p<0.05) are correlated with entrepreneurial intention, while concern (r=-.19, p<0.01), control (r=-.16, p<0.01), curiosity (r=-.23, p<0.01), and confidence (r=-.19, p<0.01) are negatively related to risk aversion; concern is significantly correlated to entrepreneurial opportunity (r=.15, p<0.01).
Meanwhile, risk aversion is negatively related to career adaptability (r = -.23, p < 0.01) and entrepreneurial opportunity (r = -.21, p < 0.01). As for the control variables, gender and age, only gender has a relation with certain variables, such as entrepreneurial intention (r = .24,
p < 0.01) and entrepreneurial opportunity (r = .25, p < 0.01). In the study, female was coded as 0, while male as 1. Therefore, the result indicates a higher association of male to entrepreneurial opportunity and intention.
Table 4.2.
Mean, Standard Deviation, Correlation, and Reliability among the Variables (N = 295)
Variables Mean S.D. 1 2 3 4 5 6 7 8 9
1 Gender .34 .47
2 Age 31.54 7.23 .09
3 EI-Entrepreneurial Intention
2.35 1.08 .24** -.02 (.95) 4 CA-Career Adaptability 5.51 .80 .07 .01 .15** (.91)
5 Concern 5.22 .92 .07 -.02 .22** .85** (.62)
6 Control 5.56 .90 .04 .01 .07 .88** .64** (.73)
7 Curiosity 5.60 .90 .10 .04 .15* .92** .71** .75** (.80)
8 Confidence 5.63 .87 .04 .02 .08 .90** .66** .73** .83** (.77)
5 EO-Entrepreneurial Opportunity
2.08 .97 .25** .06 .61** .09 .15** .02 .10 .04 (.87)
6 RA-Risk Aversion 3.20 .58 -.04 .03 -.23** -.19* -.15** -.15** -.19** -.18** -.13* (.70) Note: Number in the parentheses represent the Cronbach’s Alpha value of the variables.
*p < 0.05 **p < 0.01; Gender: Male = 1, Female = 0.
Hypotheses Testing
In this study, hierarchical regression analysis is selected to test the Hypotheses.
Hierarchical regression is applied in the analyzing process to test the relationship among the variables and verifies the relation of independent variable and dependent variable under the moderating effect. First, to control the effect of the covariates, which are age and gender, the control variables will be placed in the first model of each hierarchical regression analysis.
According to Table 4.3, in the second model, the relation of career adaptability and entrepreneurial intention is presented, which shows career adaptability significantly and positively predicts the dependent variable, entrepreneurial intention (β = .132, p < .05). The first Hypothesis, which states career adaptability is positively related to entrepreneurial intention, is supported.
The second Hypothesis states that the effect of risk aversion weakens the relationship of career adaptability and entrepreneurial intention. Corresponded to the second Hypothesis, as shown in Table 4.3, the moderator shows a significant and negative impact on the criterion, entrepreneurial intention (β = -.203, p < .001); however, as shown in model 4, the interaction of career adaptability and risk aversion does not have a significant impact on entrepreneurial intention (β = -.064, n.s.). Therefore, Hypothesis 2 is not supported.
Table 4.3.
Summary of Hierarchical Regression Result for the Moderating Effect of Risk Aversion for Variables Predicting Entrepreneurial Intention
CA-Career Adaptability .132* .093 .0.90
RA-Risk Aversion -.203*** -.227*** opportunity will strengthen the relationship of career adaptability and entrepreneurial intention, is shown in Table 4.4. In model 4, career adaptability is not related to entrepreneurial intention (β =.088, n.s.), but entrepreneurial opportunity is significantly and positively related (β = .591, p < .001). However, the interaction of career adaptability and entrepreneurial opportunity has
no significance (β = -.025, n.s.) to the criterion. As a result, entrepreneurial opportunity has no moderating effect toward the relationship between the independent and dependent variables.
Hypothesis 3 is rejected.
Table 4.4.
Summary of Hierarchical Regression Result for the Moderating Effect of Entrepreneurial Opportunity for Variables Predicting Entrepreneurial Intention
Entrepreneurial Intention
Variables Model 1 Model 2 Model 3 Model4
Control Variables
Gender .254*** .244*** .101* .100*
Age -.044 -.046 -.072 -.071
Main Effects
CA-Career Adaptability .132* .088 .088
EO-Entrepreneurial Opportunity .586*** .591***
Interaction of CA & EO -.025
F 9.990*** 8.599*** 48.309*** 38.613***
R2 .064 .081 .400 .400
Adj. R2 .058 .072 .392 .390
𝛥R2 .064 .017 .318 .001
N 295 295 295 295
Note: *p < 0.05, **p < 0.01, ***p < 0.001.
Although the study was to investigate that entrepreneurial intention and career adaptability is positively related, the study revealed the relation of entrepreneurial intention and career adaptability at dimensional level. Table 4.5 presented the result of entrepreneurial intention with each dimension of career adaptability. As displayed, concern (β = .209, p < .001) and curiosity (β = .127, p < .05) is significantly related to entrepreneurial intention. While the other two dimensions, control (β = .063, n.s.) and confidence (β = .070, n.s.), was not correlated to entrepreneurial intention.
Table 4.5
Summary of Hierarchical Regression Result for Career Adaptability at Dimensional Level for Variables Predicting Entrepreneurial Intention
As previous research stated that gender has a difference in possessing the intention of becoming an entrepreneur; thus, the study conducted the independent-sample t-test to investigate the difference between male and female groups in the level of entrepreneurial intention. The result shows that the level of entrepreneurial intention has a significant difference between male (M = 2.73, SD = 1.11) and female (M = 2.16, SD = 1.01); t(293) = 4.40, p < .001. As a result, male has higher entrepreneurial intention then female in Taiwan.
Table 4.6.
Summary of Independent t-test Result of Gender Difference in the Level of Entrepreneurial Intention
Mean (SD)
df t p
Male (N = 99) Female (N = 196) Entrepreneurial
intention
2.73 (1.11) 2.16 (1.01) 293 4.40 0.000
One-way ANOVA
One-way ANOVA is conducted in the study to compare whether there is a difference between the career status of full-time, part-time (including temporary worker, contractor, and seasonal worker), dual career, and unemployed groups, in the level of entrepreneurial intention.
The result in Table 4.6 shows there is a significant difference of entrepreneurial intention between career status (F(14,331) = 4.01, p < .01). A Tukey HSD post hoc test, shown in Table 4.7, reveals there is a significantly higher entrepreneurial intention for being a part-time worker (M = 2.94, p < .05) comparing with the full-time workers (M = 2.23). While significant differences in between the other career status groups are not found.
Table 4.7.
Summary of One-way ANOVA Result of Career Status Difference in the Level of Entrepreneurial Intention
SS df MS F p
Between Groups 13.671 3 4.557 4.013 0.008
Within Groups 330.429 291 1.135
Total 344.100 294
Table 4.8.
Summary of Tukey HSD Comparisons in the Level of Entrepreneurial Intention from Four Career Status Groups
Tukey HSD Comparisons (p-value)
Group n Full-time Full-time &
Part-time
Part time/ Contractor/
Seasonal/ Temporary
Full-time 218
Full-time &
Part-time
32 .12
Part-time/
Contractor/
Seasonal/
Temporary
18 .03* .83
Unemployment 27 .52 .94 .57
Note: *p < 0.05.