As a result of examining Pearson’s correlation coefficient to determine the correlation between agro-entrepreneurial intention and 6th industry entrepreneurship, as shown in Table
6, agro-entrepreneurial intention only showed a positive correlation with innovation (r=.192), social responsibility (r=.271), networking capabilities (r=.143), and initiative (r=.185) among 6th industry entrepreneurship, with very low correlation.
1) Moderating effect of succession status on the effect of agro-entrepreneurial intention according to entrepreneurship
The following is the result of hierarchical multiple regression analysis on the effect on entrepreneurial intention according to entrepreneurship. As shown in Table
7, in Model 1, 6th industry entrepreneurship had a significant effect on agro-entrepreneurial intention, which became stronger with higher innovation, social responsibility, network capabilities, and initiative in particular. The explanatory power of this model is 15.8%, and the regression model turned out to be statistically significant (F=7.421,
p<.001). However, risk sensitivity failed to follow normality, and thus Model 2 that excluded risk sensitivity showed similar results as Model 1. In other words, even though risk sensitivity was excluded, higher innovation, social responsibility, network capabilities, and initiative led to stronger agro-entrepreneurial intention. Challenge spirit turned out not to affect agro-entrepreneurial intention at all.
Table 7
Analyze the Influence of agro-entrepreneurial intention on 6th industry entrepreneurship (multiple regression analysis).
|
Agro-entrepreneurial intention |
|
Model 1 |
Model 2 |
Model 3 |
Model 4 |
|
|
|
|
β |
t |
p
|
β |
t |
p
|
β |
t |
p
|
β |
t |
p
|
|
Innovation (A) |
.181 |
3.025**
|
.003 |
.179 |
3.005**
|
.003 |
.132 |
2.154*
|
.032 |
.137 |
2.235*
|
.026 |
Social responsibility (B) |
.262 |
4.394***
|
.000 |
.263 |
4.411***
|
.000 |
.195 |
3.167**
|
.002 |
.194 |
3.143**
|
.002 |
Challenge spirit (C) |
-.001 |
-.014 |
.989 |
-.001 |
-.015 |
.988 |
.030 |
.498 |
.619 |
.030 |
.499 |
.618 |
Risk sensitivity (D) |
.036 |
.602 |
.548 |
|
|
|
|
|
|
|
|
|
Networking capabilities (E) |
.137 |
2.302*
|
.022 |
.145 |
2.296*
|
.023 |
.097 |
1.555 |
.121 |
.099 |
1.587 |
.114 |
Initiative (F) |
.172 |
2.879**
|
.004 |
.186 |
2.866*
|
.005 |
.102 |
1.723 |
.086 |
.105 |
1.778 |
.077 |
Successive Students (X) |
|
|
|
|
|
|
|
|
|
.272 |
4.170***
|
.000 |
A*X |
|
|
|
|
|
|
|
|
|
-.012 |
-.165 |
.869 |
B*X |
|
|
|
|
|
|
|
|
|
.003 |
.036 |
.971 |
C*X |
|
|
|
|
|
|
|
|
|
-.070 |
-.967 |
.335 |
D*X |
|
|
|
|
|
|
|
|
|
|
|
|
E*X |
|
|
|
|
|
|
|
|
|
.019 |
.282 |
.778 |
F*X |
|
|
|
|
|
|
|
|
|
.108 |
1.261 |
.209 |
|
Statistics value |
R=.398 |
R=.396 |
R=.502 |
R=.511 |
R2=.158 Adj. R2=.137 |
R2=.157 Adj. R2=.139 |
R2=.252 Adj. R2=.223 |
R2=.262 Adj. R2=.227 |
F=7.421***, p=.000 |
F=8.857***, p=.000 |
F=13.335***, p=.000 |
F=7.470***, p=.000 |
Next, in Model 3 that excluded risk sensitivity and included the moderating variable of successive students, networking capabilities among 6th industry entrepreneurship turned out not to have a significant effect on agro-entrepreneurial intention with the significance level of 10%. However, this factor can be considered if there are many samples at this level. In addition, Model 3 that included succession status had an increased explanatory variable of 9.5% compared to Model 2, which shows the importance of the factor.
In Model 4, which included the interaction effect between independent variables and succession status, there was no interaction effect by all 6th industry entrepreneurship factors and succession status, with only the main effect by succession status. VIF of the final model was 1.104~2.296 and Dubin-Watson=1.716, showing that there is no multicollinearity of this model, and the explanatory power of the model was 26.2%.
However, as a result of residual analysis of this model, some measures were slightly off the normality on p-p plot (Fig.
3). For this reason, an additional logistics regression analysis was conducted by distinguishing the case with agroentrepreneurial intention and the case with no intention by dividing the dependent variables into two cases.
Figure 3
P-P plot of the standarized observed and expected values.
As shown in Table
8, in Model 5 that included risk sensitivity, higher innovation and social responsibility among 6th industry entrepreneurship led to more agro-entrepreneurial intention. Initiative served as a positive factor at the significance level of 10%. The explanatory power of the model was 11.3% (Cox & Snell R2) and the classification accuracy was 77.7%. However, Model 6 that excluded risk sensitivity showed similar results as Model 5, and the classification accuracy of the model was increased by 0.1% to 77.9%.
Table 8
Analyze the influence of agro-entrepreneurial intention on 6th Industry entrepreneurship (logistic-regression analysis).
|
Agro-entrepreneurial intention (Yes=1, No=0) |
|
Model 5 |
Model 6 |
Model 7 |
Model 8 |
|
|
|
|
Exp (B) |
Wals |
p
|
Exp (B) |
Wals |
p
|
Exp (B) |
Wals |
p
|
Exp (B) |
Wals |
p
|
|
Innovation (A) |
1.726 |
8.997**
|
.003 |
1.716 |
8.870**
|
.003 |
1.690 |
7.836**
|
.005 |
1.530 |
4.016*
|
.045 |
Social responsibility (B) |
1.815 |
11.051**
|
.001 |
1.799 |
10.916**
|
.001 |
1.690 |
8.205**
|
.004 |
1.796 |
7.744**
|
.005 |
Challenge spirit (C) |
.902 |
.321 |
.571 |
.887 |
.436 |
.509 |
.915 |
.225 |
.636 |
.958 |
.044 |
.834 |
Risk sensitivity (D) |
1.098 |
.353 |
.552 |
|
|
|
|
|
|
|
|
|
Networking capabilities (E) |
1.311 |
2.636 |
.104 |
1.308 |
2.603 |
.107 |
1.231 |
1.505 |
.220 |
1.353 |
2.353 |
.125 |
Initiative (F) |
1.387 |
3.426 |
.064 |
1.367 |
3.218 |
.073 |
1.265 |
1.660 |
.198 |
1.175 |
.713 |
.399 |
Successive Students (X) |
|
|
|
|
|
|
3.279 |
8.941**
|
.003 |
2.389 |
2.547 |
.111 |
A*X |
|
|
|
|
|
|
|
|
|
1.451 |
.400 |
.527 |
B*X |
|
|
|
|
|
|
|
|
|
.270 |
4.484*
|
.034 |
C*X |
|
|
|
|
|
|
|
|
|
.153 |
3.442 |
.064 |
D*X |
|
|
|
|
|
|
|
|
|
|
|
|
E*X |
|
|
|
|
|
|
|
|
|
.430 |
2.312 |
.128 |
F*X |
|
|
|
|
|
|
|
|
|
21.187 |
5.144*
|
.023 |
|
Statistics value |
-2LL=236.141 |
-2LL=236.496 |
-2LL=227.782 |
-2LL=215.604 |
Cox & Snell R2=.113 |
Cox & Snell R2=.111 |
Cox & Snell R2=.142 |
Cox & Snell R2=.184 |
Nagelkerke R2=.170 |
Nagelkerke R2=.168 |
Nagelkerke R2=.215 |
Nagelkerke R2=.278 |
χ2=29.134***, p=.000 |
χ2=28.780***, p=.000 |
χ2=37.494***, p=.000 |
χ2=49.671***, p=.000 |
classification accuracy: |
classification accuracy: |
classification accuracy: |
classification accuracy: |
77.7% |
77.9% |
79.1% |
79.5% |
Therefore, for Model 7 that included succession status, this served as the biggest factor, and only innovation and social responsibility served as a highly important factor as 6th industry entrepreneurship. The explanatory power of the model was increased by 3.1% to 14.2%, and the classification accuracy was 79.1%.
To verify the moderating effect of succession status, Model 8 included the interaction effect between succession status and 6th industry entrepreneurship, which showed a different effect from the aforementioned hierarchical analysis. In the multiple regression analysis, there was no interaction effect between succession status and independent variables, but logistics regression analysis showed interaction effect between social responsibility and successive students, and initiative and successive students. The interaction effect between challenge spirit and successive students also appeared at the significance level of 10%.
In other words, as shown in Table
9, successive students are accompanied by initiative and challenge spirit, whereas non-successive students are only significantly affected by innovation and social responsibility, without any effect from initiative and challenge spirit. Thus, for students whose parents are not engaged in agriculture, innovation and social responsibility are the most important factors, and their agro-entrepreneurial intention can be increased by nurturing these factors. On the other hand, for students whose parents are engaged in agriculture, they need initiative and challenge spirit more than others.
Table 9
Logistic-regression analysis of 6th industry entrepreneurship Influenced by family business.
|
Non-successive Students |
Successive Studen |
|
|
Exp (B) |
Wals |
p
|
Exp (B) |
Wals |
p
|
|
Innovation (A) |
1.530 |
4.016**
|
.045 |
2.221 |
2.112 |
.146 |
Social responsibility (B) |
1.796 |
7.744**
|
.005 |
.485 |
1.548 |
.213 |
Challenge spirit (C) |
.958 |
.044 |
.834 |
.146 |
3.760 |
.052 |
Risk sensitivity (D) |
|
|
|
|
|
|
Networking capabilities (E) |
1.353 |
2.353 |
.125 |
.582 |
1.090 |
.297 |
Initiative (F) |
1.174 |
.713 |
.399 |
24.896 |
5.818*
|
.016 |
|
Statistics value |
-2LL=178.544 |
-2LL=37.061 |
Cox & Snell R2=.069 |
Cox & Snell R2=.369 |
Nagelkerke R2=.113 |
Nagelkerke R2=.491 |
χ2=14.631***, p=.000 |
χ2=18.391***, p=.002 |
classification accuracy: 81.4% |
classification accuracy: 70.0% |
It has been reported that home environment and satisfaction in entrepreneurship education have an indirect effect on entrepreneurial intention mediated by career orientation (
Park et al., 2011). To encourage entrepreneurial intention of college students, it is most important to nurture entrepreneurship through entrepreneurship education (
Shim and Lee, 2015). In sum, to encourage systematic agro-entrepreneurial intention of new agricultural workers through college education, it is necessary to provide systematic education of customized entrepreneurship in association with the occupations of the students’ parents to instill entrepreneurial intention, through which agricultural startups will increase.