*4.5. Moderation Results*

The moderation analysis aimed to establish if gender, income, and city moderate the relationship and impact among independent and mediation, leading to dependent variables. Firstly, gender, income, and city coded as dummy variables. A correlation analysis performed between the dependent variable and dummy coded variables from gender, income, and city to establish which variables might be potential moderators. The only significant correlation obtained between PB and the dummy variable of Income Group 3, i.e., with an income between PKR 64,001-150,000 (*r* = 0.065, *p* = 0.047). Therefore, the dummy variable of Income Group 3 shortlisted as a potential moderator variable. First, a regression model (Block 1) fitted to predict PB using PI (purchase intention) and the dummy variable of Income Group 3. The regression model found to be significant (*r*-square = 0.586). The model coefficients are shown in Table 9; both the main effects of PI and the dummy variable of Income Group 3 were found to be significant.



Next, the interaction between PI and the dummy variable of Income Group 3 added to the Block 1 model, this constituted the Block 2 model. The regression model was found to be significant (r-square = 0.586). The model coefficients shown in Table 10, after adding the interaction term, the main effect of PI was still substantial but the main impact of the dummy variable of Income Group 3 was not significant anymore. It indicates that the dummy variable of Income Group 3 moderates the relationship between PI and PB, but the main effect of PI is also substantial.

**Table 10.** Block 2 regression model.

