Equbusiness book VERSION 28SEPT2023 - Flipbook - Page 78
The results of the regression analysis conducted to test hypotheses H1 and H3 are presented in Table 5.
Table 5. Linear regression results (Model 1)
ROA
WOB
RD
TA
LEV
Constant
Coef.
.001
.354
.029
-.307
-.002
Mean dependent var
R-squared
F-test
Akaike crit. (AIC)
*** p
F= 0.000), and the independent variables in the
model explain 12,7% of the change in ROA. There is no statistically significant relationship between WOB, RD and
ROA. In other words, the percentage of women on boards does not affect the firm's financial performance.
Hypotheses H1 and H3 are accepted. However, there is a relationship between LEV and ROA at a 1% significance
level. 0.303 unit increase in LEV leads to a 1 unit decrease in ROA. In addition to this, there is a relationship
between TA and ROA at a 5% significance level.
The results of the regression analysis conducted to test hypotheses H2 and H3 are presented in Table 6.
Table 6. Linear regression results (Model 2)
ROA
IWOB
RD
TA
LEV
Constant
Mean dependent var
R-squared
F-test
Akaike crit. (AIC)
*** p
F= 0.000), and the independent variables in the
model explain 12.4% of the change in ROA. There is no statistically significant relationship between IWOB, RD and
ROA. In other words, the percentage of women among the independent members of the board of directors has
no effect on the firm's financial performance. Hypotheses H2 and H3 are accepted.
