Reliability
Table 4.5
Reliability Test
Variable Cronbach’s Alpha N of Items Remark
Brand Awareness 0.825 5 Reliable
Brand Association 0.757 3 Reliable
Perceived Quality 0.763 4 Reliable
Brand Loyalty 0.890 5 Reliable
After validity test, this is the result of the reliability test. The requirement to be reliable is the Cronbach’s Alpha must be more than 0.7. As seen from the table 4.5 the Cronbach’s Alpha of every variables are more than 0.7 which are remarked as reliable. To be explained, the Cronbach’s Alpha value of Brand Awareness is 0.825, Brand Association’s value is 0.757, the Cronbach’s Alpha of Perceived Quality value is 0.763, and the last variable Brand Loyalty Cronbach’s Alpha has 0.890 value.
4.3 Structural Equation Modeling (SEM) …show more content…
The table 4.6 shows the result of SEM Model Fit. Measuring the Chi-square is the first step to indicates wheter the model fits the data or indicates the different between the estimated population covariance and the sample covariance. The smaller value of Chi-square means the value are more better. As seen from the table above the Chi-quare value is 0.000 which means the value is significant. The value also means that the difference of estimated population covariance and the sample covariance is very low, or can be concluded as equal.
The next step is measuring the value of CMIN/DF, which means the Chi-square divided by degree of freedom. Table 4.6 above shows the value of CMIN/DF is 1.926, can be obtained from the discrepancy divided by degrees of freedom (344.733 / 179 = 1.926). Therefore the model is good …show more content…
As seen from the table 4.7 above the P value of Brand Loyalty is ***, maeans the probability of getting a critical ratio as large as 4.249 in absolute value is less than 0.001. In other words, the regression weight for Brand Loyalty towards Purchasing Decision is significantly different from zero at the 0.001 level (two-tailed). Thus the hypothesis of Brand Loyalty towards Purchase Decision is significant and supported by the data.
The other significance of the data can be shown from table 4.7, which is Perceived Quality. The probability of getting a critical ratio as large as 2.961 in absolute value is less than 0.003. In other words, the regression weight for Perceived Quality towards Purchasing Decision is significantly different from zero at the 0.01 level (two-tailed). Thus the hypothesis of Perceived Quality towards Purchase Decision is significant and supported by the data.
The next data as can be seen from the table 4.7 above is the P value of Brand Awareness is 0.926. This means the probability of getting a critical ratio as large as 0.093 in absolute value is 0.926. In other words, the regression weight of Brand Awareness in the prediction of Purchasing Decision is not significantly different from zero at the 0.05 level (two-tailed). Thus the hypothesis of Brand Awareness towards Purchase Decision is not supported by the data and not
Table 4.5
Reliability Test
Variable Cronbach’s Alpha N of Items Remark
Brand Awareness 0.825 5 Reliable
Brand Association 0.757 3 Reliable
Perceived Quality 0.763 4 Reliable
Brand Loyalty 0.890 5 Reliable
After validity test, this is the result of the reliability test. The requirement to be reliable is the Cronbach’s Alpha must be more than 0.7. As seen from the table 4.5 the Cronbach’s Alpha of every variables are more than 0.7 which are remarked as reliable. To be explained, the Cronbach’s Alpha value of Brand Awareness is 0.825, Brand Association’s value is 0.757, the Cronbach’s Alpha of Perceived Quality value is 0.763, and the last variable Brand Loyalty Cronbach’s Alpha has 0.890 value.
4.3 Structural Equation Modeling (SEM) …show more content…
The table 4.6 shows the result of SEM Model Fit. Measuring the Chi-square is the first step to indicates wheter the model fits the data or indicates the different between the estimated population covariance and the sample covariance. The smaller value of Chi-square means the value are more better. As seen from the table above the Chi-quare value is 0.000 which means the value is significant. The value also means that the difference of estimated population covariance and the sample covariance is very low, or can be concluded as equal.
The next step is measuring the value of CMIN/DF, which means the Chi-square divided by degree of freedom. Table 4.6 above shows the value of CMIN/DF is 1.926, can be obtained from the discrepancy divided by degrees of freedom (344.733 / 179 = 1.926). Therefore the model is good …show more content…
As seen from the table 4.7 above the P value of Brand Loyalty is ***, maeans the probability of getting a critical ratio as large as 4.249 in absolute value is less than 0.001. In other words, the regression weight for Brand Loyalty towards Purchasing Decision is significantly different from zero at the 0.001 level (two-tailed). Thus the hypothesis of Brand Loyalty towards Purchase Decision is significant and supported by the data.
The other significance of the data can be shown from table 4.7, which is Perceived Quality. The probability of getting a critical ratio as large as 2.961 in absolute value is less than 0.003. In other words, the regression weight for Perceived Quality towards Purchasing Decision is significantly different from zero at the 0.01 level (two-tailed). Thus the hypothesis of Perceived Quality towards Purchase Decision is significant and supported by the data.
The next data as can be seen from the table 4.7 above is the P value of Brand Awareness is 0.926. This means the probability of getting a critical ratio as large as 0.093 in absolute value is 0.926. In other words, the regression weight of Brand Awareness in the prediction of Purchasing Decision is not significantly different from zero at the 0.05 level (two-tailed). Thus the hypothesis of Brand Awareness towards Purchase Decision is not supported by the data and not